37-Issue 2

Permanent URI for this collection

Curves and Details
Feature Curve Co-Completion in Noisy Data
Anne Gehre, Isaak Lim, and Leif Kobbelt
Wavejets: A Local Frequency Framework for Shape Details Amplification
Yohann Béarzi, Julie Digne, and Raphaëlle Chaine
Repairing Inconsistent Curve Networks on Non-parallel Cross-sections
Zhi Yang Huang, Michelle Holloway, Nathan Carr, and Tao Ju
It's all About Light
ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content
Demetris Marnerides, Thomas Bashford-Rogers, Jon Hatchett, and Kurt Debattista
From Faces to Outdoor Light Probes
Dan A. Calian, Jean-François Lalonde, Paulo Gotardo, Tomas Simon, Iain Matthews, and Kenny Mitchell
Multiple Scattering in Inhomogeneous Participating Media Using Rao-Blackwellization and Control Variates
László Szirmay-Kalos, Milán Magdics, and Mateu Sbert
Geometry Learning
PCPNet: Learning Local Shape Properties from Raw Point Clouds
Paul Guerrero, Yanir Kleiman, Maks Ovsjanikov, and Niloy J. Mitra
PointProNets: Consolidation of Point Clouds with Convolutional Neural Networks
Riccardo Roveri, A. Cengiz Öztireli, Ioana Pandele, and Markus Gross
Terrain Super-resolution through Aerial Imagery and Fully Convolutional Networks
Oscar Argudo, Antonio Chica, and Carlos Andujar
Material Appearance
A New Microflake Model With Microscopic Self-shadowing for Accurate Volume Downsampling
Guillaume Loubet and Fabrice Neyret
Real-Time Rendering of Wave-Optical Effects on Scratched Surfaces
Zdravko Velinov, Sebastian Werner, and Matthias B. Hullin
A Versatile Parameterization for Measured Material Manifolds
Cyril Soler, Kartic Subr, and Derek Nowrouzezahrai
Simulating Fluids
A Physically Consistent Implicit Viscosity Solver for SPH Fluids
Marcel Weiler, Dan Koschier, Magnus Brand, and Jan Bender
Fast Fluid Simulations with Sparse Volumes on the GPU
Kui Wu, Nghia Truong, Cem Yuksel, and Rama Hoetzlein
Extended Narrow Band FLIP for Liquid Simulations
Takahiro Sato, Chris Wojtan, Nils Thuerey, Takeo Igarashi, and Ryoichi Ando
Mapping and Analysis
Improved Functional Mappings via Product Preservation
Dorian Nogneng, Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael Bronstein, and Maks Ovsjanikov
Gaze and Attention
Visual Attention for Rendered 3D Shapes
Guillaume Lavoué, Frédéric Cordier, Hyewon Seo, and Mohamed-Chaker Larabi
Watch to Edit: Video Retargeting using Gaze
Kranthi Kumar Rachavarapu, Moneish Kumar, Vineet Gandhi, and Ramanathan Subramanian
GazeDirector: Fully Articulated Eye Gaze Redirection in Video
Erroll Wood, Tadas Baltrušaitis, Louis-Philippe Morency, Peter Robinson, and Andreas Bulling
Collision and Motion
Efficient BVH-based Collision Detection Scheme with Ordering and Restructuring
Xinlei Wang, Min Tang, Dinesh Manocha, and Ruofeng Tong
Fast Penetration Volume for Rigid Bodies
Dan Nirel and Dani Lischinski
Computational Fabrication
Packable Springs
Katja Wolff, Roi Poranne, Oliver Glauser, and Olga Sorkine-Hornung
String Art: Towards Computational Fabrication of String Images
Michael Birsak, Florian Rist, Peter Wonka, and Przemyslaw Musialski
Watercolor Woodblock Printing with Image Analysis
Athina Panotopoulou, Sylvain Paris, and Emily Whiting
Motion and Control
Real-time Locomotion Controller using an Inverted-Pendulum-based Abstract Model
Jaepyung Hwang, Jongmin Kim, Il Hong Suh, and Taesoo Kwon
Self-similarity Analysis for Motion Capture Cleaning
Andreas Aristidou, Daniel Cohen-Or, Jessica K. Hodgins, and Ariel Shamir
Aura Mesh: Motion Retargeting to Preserve the Spatial Relationships between Skinned Characters
Taeil Jin, Meekyoung Kim, and Sung-Hee Lee
Segmentation and Noise
Flexible Live-Wire: Image Segmentation with Floating Anchors
Brian Summa, Noura Faraj, Cody Licorish, and Valerio Pascucci
Semantic Segmentation for Line Drawing Vectorization Using Neural Networks
Byungsoo Kim, Oliver Wang, A. Cengiz Öztireli, and Markus Gross
Sequences with Low-Discrepancy Blue-Noise 2-D Projections
Hélène Perrier, David Coeurjolly, Feng Xie, Matt Pharr, Pat Hanrahan, and Victor Ostromoukhov
Physical Simulation
Hair Modeling and Simulation by Style
Seunghwan Jung and Sung-Hee Lee
Image Magic
Practical Radiometric Compensation for Projection Display on Textured Surfaces using a Multidimensional Model
Yuqi Li, Aditi Majumder, Meenakshisundaram Gopi, Chong Wang, and Jieyu Zhao
Single-image Tomography: 3D Volumes from 2D Cranial X-Rays
Philipp Henzler, Volker Rasche, Timo Ropinski, and Tobias Ritschel
Deep Joint Design of Color Filter Arrays and Demosaicing
Bernardo Henz, Eduardo S. L. Gastal, and Manuel M. Oliveira
Procedural Modeling
Example-based Authoring of Procedural Modeling Programs with Structural and Continuous Variability
Daniel Ritchie, Sarah Jobalia, and Anna Thomas
Procedural Modeling of a Building from a Single Image
Gen Nishida, Adrien Bousseau, and Daniel G. Aliaga
Procedural Cloudscapes
Antoine Webanck, Yann Cortial, Eric Guérin, and Eric Galin
Optimized Rendering
Approximate Program Smoothing Using Mean-Variance Statistics, with Application to Procedural Shader Bandlimiting
Yuting Yang and Connelly Barnes
Fast Catmull-Rom Spline Interpolation for High-Quality Texture Sampling
Balázs Csébfalvi
Parallel Reinsertion for Bounding Volume Hierarchy Optimization
Daniel Meister and Jiří Bittner
Perception and Senses
Motion Sickness Simulation Based on Sensorimotor Control
Chen-Hui Hu and Wen-Chieh Lin
Modeling and Visualization
Controllable Dendritic Crystal Simulation Using Orientation Field
Bo Ren, Jiahui Huang, Ming C. Lin, and Shi-Min Hu
Interactive Generation of Time-evolving, Snow-Covered Landscapes with Avalanches
Guillaume Cordonnier, Pierre Ecormier, Eric Galin, James Gain, Bedrich Benes, and Marie-Paule Cani
MIQP-based Layout Design for Building Interiors
Wenming Wu, Lubin Fan, Ligang Liu, and Peter Wonka

BibTeX (37-Issue 2)
                
@article{
10.1111:cgf.13381,
journal = {Computer Graphics Forum}, title = {{
EUROGRAPHICS 2018: CGF 37-2 Frontmatter}},
author = {
Gutierrez, Diego
and
Sheffer, Alla
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
DOI = {
10.1111/cgf.13381}
}
                
@article{
10.1111:cgf.13337,
journal = {Computer Graphics Forum}, title = {{
Feature Curve Co-Completion in Noisy Data}},
author = {
Gehre, Anne
and
Lim, Isaak
and
Kobbelt, Leif
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13337}
}
                
@article{
10.1111:cgf.13339,
journal = {Computer Graphics Forum}, title = {{
Repairing Inconsistent Curve Networks on Non-parallel Cross-sections}},
author = {
Huang, Zhi Yang
and
Holloway, Michelle
and
Carr, Nathan
and
Ju, Tao
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13339}
}
                
@article{
10.1111:cgf.13338,
journal = {Computer Graphics Forum}, title = {{
Wavejets: A Local Frequency Framework for Shape Details Amplification}},
author = {
Béarzi, Yohann
and
Digne, Julie
and
Chaine, Raphaëlle
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13338}
}
                
@article{
10.1111:cgf.13340,
journal = {Computer Graphics Forum}, title = {{
ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content}},
author = {
Marnerides, Demetris
and
Bashford-Rogers, Thomas
and
Hatchett, Jon
and
Debattista, Kurt
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13340}
}
                
@article{
10.1111:cgf.13341,
journal = {Computer Graphics Forum}, title = {{
From Faces to Outdoor Light Probes}},
author = {
Calian, Dan A.
and
Lalonde, Jean-François
and
Gotardo, Paulo
and
Simon, Tomas
and
Matthews, Iain
and
Mitchell, Kenny
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13341}
}
                
@article{
10.1111:cgf.13342,
journal = {Computer Graphics Forum}, title = {{
Multiple Scattering in Inhomogeneous Participating Media Using Rao-Blackwellization and Control Variates}},
author = {
Szirmay-Kalos, László
and
Magdics, Milán
and
Sbert, Mateu
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13342}
}
                
@article{
10.1111:cgf.13343,
journal = {Computer Graphics Forum}, title = {{
PCPNet: Learning Local Shape Properties from Raw Point Clouds}},
author = {
Guerrero, Paul
and
Kleiman, Yanir
and
Ovsjanikov, Maks
and
Mitra, Niloy J.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13343}
}
                
@article{
10.1111:cgf.13344,
journal = {Computer Graphics Forum}, title = {{
PointProNets: Consolidation of Point Clouds with Convolutional Neural Networks}},
author = {
Roveri, Riccardo
and
Öztireli, A. Cengiz
and
Pandele, Ioana
and
Gross, Markus
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13344}
}
                
@article{
10.1111:cgf.13345,
journal = {Computer Graphics Forum}, title = {{
Terrain Super-resolution through Aerial Imagery and Fully Convolutional Networks}},
author = {
Argudo, Oscar
and
Chica, Antonio
and
Andujar, Carlos
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13345}
}
                
@article{
10.1111:cgf.13346,
journal = {Computer Graphics Forum}, title = {{
A New Microflake Model With Microscopic Self-shadowing for Accurate Volume Downsampling}},
author = {
Loubet, Guillaume
and
Neyret, Fabrice
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13346}
}
                
@article{
10.1111:cgf.13347,
journal = {Computer Graphics Forum}, title = {{
Real-Time Rendering of Wave-Optical Effects on Scratched Surfaces}},
author = {
Velinov, Zdravko
and
Werner, Sebastian
and
Hullin, Matthias B.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13347}
}
                
@article{
10.1111:cgf.13348,
journal = {Computer Graphics Forum}, title = {{
A Versatile Parameterization for Measured Material Manifolds}},
author = {
Soler, Cyril
and
Subr, Kartic
and
Nowrouzezahrai, Derek
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13348}
}
                
@article{
10.1111:cgf.13349,
journal = {Computer Graphics Forum}, title = {{
A Physically Consistent Implicit Viscosity Solver for SPH Fluids}},
author = {
Weiler, Marcel
and
Koschier, Dan
and
Brand, Magnus
and
Bender, Jan
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13349}
}
                
@article{
10.1111:cgf.13350,
journal = {Computer Graphics Forum}, title = {{
Fast Fluid Simulations with Sparse Volumes on the GPU}},
author = {
Wu, Kui
and
Truong, Nghia
and
Yuksel, Cem
and
Hoetzlein, Rama
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13350}
}
                
@article{
10.1111:cgf.13351,
journal = {Computer Graphics Forum}, title = {{
Extended Narrow Band FLIP for Liquid Simulations}},
author = {
Sato, Takahiro
and
Wojtan, Chris
and
Thuerey, Nils
and
Igarashi, Takeo
and
Ando, Ryoichi
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13351}
}
                
@article{
10.1111:cgf.13352,
journal = {Computer Graphics Forum}, title = {{
Improved Functional Mappings via Product Preservation}},
author = {
Nogneng, Dorian
and
Melzi, Simone
and
Rodolà, Emanuele
and
Castellani, Umberto
and
Bronstein, Michael
and
Ovsjanikov, Maks
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13352}
}
                
@article{
10.1111:cgf.13353,
journal = {Computer Graphics Forum}, title = {{
Visual Attention for Rendered 3D Shapes}},
author = {
Lavoué, Guillaume
and
Cordier, Frédéric
and
Seo, Hyewon
and
Larabi, Mohamed-Chaker
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13353}
}
                
@article{
10.1111:cgf.13354,
journal = {Computer Graphics Forum}, title = {{
Watch to Edit: Video Retargeting using Gaze}},
author = {
Rachavarapu, Kranthi Kumar
and
Kumar, Moneish
and
Gandhi, Vineet
and
Subramanian, Ramanathan
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13354}
}
                
@article{
10.1111:cgf.13355,
journal = {Computer Graphics Forum}, title = {{
GazeDirector: Fully Articulated Eye Gaze Redirection in Video}},
author = {
Wood, Erroll
and
Baltrušaitis, Tadas
and
Morency, Louis-Philippe
and
Robinson, Peter
and
Bulling, Andreas
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13355}
}
                
@article{
10.1111:cgf.13356,
journal = {Computer Graphics Forum}, title = {{
Efficient BVH-based Collision Detection Scheme with Ordering and Restructuring}},
author = {
Wang, Xinlei
and
Tang, Min
and
Manocha, Dinesh
and
Tong, Ruofeng
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13356}
}
                
@article{
10.1111:cgf.13357,
journal = {Computer Graphics Forum}, title = {{
Fast Penetration Volume for Rigid Bodies}},
author = {
Nirel, Dan
and
Lischinski, Dani
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13357}
}
                
@article{
10.1111:cgf.13358,
journal = {Computer Graphics Forum}, title = {{
Packable Springs}},
author = {
Wolff, Katja
and
Poranne, Roi
and
Glauser, Oliver
and
Sorkine-Hornung, Olga
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13358}
}
                
@article{
10.1111:cgf.13359,
journal = {Computer Graphics Forum}, title = {{
String Art: Towards Computational Fabrication of String Images}},
author = {
Birsak, Michael
and
Rist, Florian
and
Wonka, Peter
and
Musialski, Przemyslaw
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13359}
}
                
@article{
10.1111:cgf.13360,
journal = {Computer Graphics Forum}, title = {{
Watercolor Woodblock Printing with Image Analysis}},
author = {
Panotopoulou, Athina
and
Paris, Sylvain
and
Whiting, Emily
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13360}
}
                
@article{
10.1111:cgf.13361,
journal = {Computer Graphics Forum}, title = {{
Real-time Locomotion Controller using an Inverted-Pendulum-based Abstract Model}},
author = {
Hwang, Jaepyung
and
Kim, Jongmin
and
Suh, Il Hong
and
Kwon, Taesoo
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13361}
}
                
@article{
10.1111:cgf.13362,
journal = {Computer Graphics Forum}, title = {{
Self-similarity Analysis for Motion Capture Cleaning}},
author = {
Aristidou, Andreas
and
Cohen-Or, Daniel
and
Hodgins, Jessica K.
and
Shamir, Ariel
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13362}
}
                
@article{
10.1111:cgf.13363,
journal = {Computer Graphics Forum}, title = {{
Aura Mesh: Motion Retargeting to Preserve the Spatial Relationships between Skinned Characters}},
author = {
Jin, Taeil
and
Kim, Meekyoung
and
Lee, Sung-Hee
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13363}
}
                
@article{
10.1111:cgf.13364,
journal = {Computer Graphics Forum}, title = {{
Flexible Live-Wire: Image Segmentation with Floating Anchors}},
author = {
Summa, Brian
and
Faraj, Noura
and
Licorish, Cody
and
Pascucci, Valerio
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13364}
}
                
@article{
10.1111:cgf.13365,
journal = {Computer Graphics Forum}, title = {{
Semantic Segmentation for Line Drawing Vectorization Using Neural Networks}},
author = {
Kim, Byungsoo
and
Wang, Oliver
and
Öztireli, A. Cengiz
and
Gross, Markus
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13365}
}
                
@article{
10.1111:cgf.13366,
journal = {Computer Graphics Forum}, title = {{
Sequences with Low-Discrepancy Blue-Noise 2-D Projections}},
author = {
Perrier, Hélène
and
Coeurjolly, David
and
Xie, Feng
and
Pharr, Matt
and
Hanrahan, Pat
and
Ostromoukhov, Victor
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13366}
}
                
@article{
10.1111:cgf.13367,
journal = {Computer Graphics Forum}, title = {{
Hair Modeling and Simulation by Style}},
author = {
Jung, Seunghwan
and
Lee, Sung-Hee
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13367}
}
                
@article{
10.1111:cgf.13368,
journal = {Computer Graphics Forum}, title = {{
Practical Radiometric Compensation for Projection Display on Textured Surfaces using a Multidimensional Model}},
author = {
Li, Yuqi
and
Majumder, Aditi
and
Gopi, Meenakshisundaram
and
Wang, Chong
and
Zhao, Jieyu
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13368}
}
                
@article{
10.1111:cgf.13369,
journal = {Computer Graphics Forum}, title = {{
Single-image Tomography: 3D Volumes from 2D Cranial X-Rays}},
author = {
Henzler, Philipp
and
Rasche, Volker
and
Ropinski, Timo
and
Ritschel, Tobias
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13369}
}
                
@article{
10.1111:cgf.13370,
journal = {Computer Graphics Forum}, title = {{
Deep Joint Design of Color Filter Arrays and Demosaicing}},
author = {
Henz, Bernardo
and
Gastal, Eduardo S. L.
and
Oliveira, Manuel M.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13370}
}
                
@article{
10.1111:cgf.13371,
journal = {Computer Graphics Forum}, title = {{
Example-based Authoring of Procedural Modeling Programs with Structural and Continuous Variability}},
author = {
Ritchie, Daniel
and
Jobalia, Sarah
and
Thomas, Anna
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13371}
}
                
@article{
10.1111:cgf.13372,
journal = {Computer Graphics Forum}, title = {{
Procedural Modeling of a Building from a Single Image}},
author = {
Nishida, Gen
and
Bousseau, Adrien
and
Aliaga, Daniel G.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13372}
}
                
@article{
10.1111:cgf.13373,
journal = {Computer Graphics Forum}, title = {{
Procedural Cloudscapes}},
author = {
Webanck, Antoine
and
Cortial, Yann
and
Guérin, Eric
and
Galin, Eric
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13373}
}
                
@article{
10.1111:cgf.13374,
journal = {Computer Graphics Forum}, title = {{
Approximate Program Smoothing Using Mean-Variance Statistics, with Application to Procedural Shader Bandlimiting}},
author = {
Yang, Yuting
and
Barnes, Connelly
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13374}
}
                
@article{
10.1111:cgf.13375,
journal = {Computer Graphics Forum}, title = {{
Fast Catmull-Rom Spline Interpolation for High-Quality Texture Sampling}},
author = {
Csébfalvi, Balázs
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13375}
}
                
@article{
10.1111:cgf.13376,
journal = {Computer Graphics Forum}, title = {{
Parallel Reinsertion for Bounding Volume Hierarchy Optimization}},
author = {
Meister, Daniel
and
Bittner, Jiří
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13376}
}
                
@article{
10.1111:cgf.13377,
journal = {Computer Graphics Forum}, title = {{
Motion Sickness Simulation Based on Sensorimotor Control}},
author = {
Hu, Chen-Hui
and
Lin, Wen-Chieh
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13377}
}
                
@article{
10.1111:cgf.13378,
journal = {Computer Graphics Forum}, title = {{
Controllable Dendritic Crystal Simulation Using Orientation Field}},
author = {
Ren, Bo
and
Huang, Jiahui
and
Lin, Ming C.
and
Hu, Shi-Min
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13378}
}
                
@article{
10.1111:cgf.13379,
journal = {Computer Graphics Forum}, title = {{
Interactive Generation of Time-evolving, Snow-Covered Landscapes with Avalanches}},
author = {
Cordonnier, Guillaume
and
Ecormier, Pierre
and
Galin, Eric
and
Gain, James
and
Benes, Bedrich
and
Cani, Marie-Paule
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13379}
}
                
@article{
10.1111:cgf.13380,
journal = {Computer Graphics Forum}, title = {{
MIQP-based Layout Design for Building Interiors}},
author = {
Wu, Wenming
and
Fan, Lubin
and
Liu, Ligang
and
Wonka, Peter
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13380}
}

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Recent Submissions

Now showing 1 - 45 of 45
  • Item
    EUROGRAPHICS 2018: CGF 37-2 Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Gutierrez, Diego; Sheffer, Alla; Gutierrez, Diego; Sheffer, Alla
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    Feature Curve Co-Completion in Noisy Data
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Gehre, Anne; Lim, Isaak; Kobbelt, Leif; Gutierrez, Diego and Sheffer, Alla
    Feature curves on 3D shapes provide important hints about significant parts of the geometry and reveal their underlying structure. However, when we process real world data, automatically detected feature curves are affected by measurement uncertainty, missing data, and sampling resolution, leading to noisy, fragmented, and incomplete feature curve networks. These artifacts make further processing unreliable. In this paper we analyze the global co-occurrence information in noisy feature curve networks to fill in missing data and suppress weakly supported feature curves. For this we propose an unsupervised approach to find meaningful structure within the incomplete data by detecting multiple occurrences of feature curve configurations (cooccurrence analysis). We cluster and merge these into feature curve templates, which we leverage to identify strongly supported feature curve segments as well as to complete missing data in the feature curve network. In the presence of significant noise, previous approaches had to resort to user input, while our method performs fully automatic feature curve co-completion. Finding feature reoccurrences however, is challenging since naïve feature curve comparison fails in this setting due to fragmentation and partial overlaps of curve segments. To tackle this problem we propose a robust method for partial curve matching. This provides us with the means to apply symmetry detection methods to identify co-occurring configurations. Finally, Bayesian model selection enables us to detect and group re-occurrences that describe the data well and with low redundancy.
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    Repairing Inconsistent Curve Networks on Non-parallel Cross-sections
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Huang, Zhi Yang; Holloway, Michelle; Carr, Nathan; Ju, Tao; Gutierrez, Diego and Sheffer, Alla
    In this work we present the first algorithm for restoring consistency between curve networks on non-parallel cross-sections. Our method addresses a critical but overlooked challenge in the reconstruction process from cross-sections that stems from the fact that cross-sectional slices are often generated independently of one another, such as in interactive volume segmentation. As a result, the curve networks on two non-parallel slices may disagree where the slices intersect, which makes these crosssections an invalid input for surfacing. We propose a method that takes as input an arbitrary number of non-parallel slices, each partitioned into two or more labels by a curve network, and outputs a modified set of curve networks on these slices that are guaranteed to be consistent. We formulate the task of restoring consistency while preserving the shape of input curves as a constrained optimization problem, and we propose an effective solution framework. We demonstrate our method on a data-set of complex multi-labeled input cross-sections. Our technique efficiently produces consistent curve networks even in the presence of large errors.
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    Wavejets: A Local Frequency Framework for Shape Details Amplification
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Béarzi, Yohann; Digne, Julie; Chaine, Raphaëlle; Gutierrez, Diego and Sheffer, Alla
    Detail enhancement is a well-studied area of 3D rendering and image processing, which has few equivalents for 3D shape processing. To enhance details, one needs an efficient analysis tool to express the local surface dynamics.We introduceWavejets, a new function basis for locally decomposing a shape expressed over the local tangent plane, by considering both angular oscillations of the surface around each point and a radial polynomial.We link theWavejets coefficients to surface derivatives and give theoretical guarantees for their precision and stability with respect to an approximate tangent plane. The coefficients can be used for shape details amplification, to enhance, invert or distort them, by operating either on the surface point positions or on the normals. From a practical point of view, we derive an efficient way of estimating Wavejets on point sets and demonstrate experimentally the amplification results with respect to noise or basis truncation.
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    ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Marnerides, Demetris; Bashford-Rogers, Thomas; Hatchett, Jon; Debattista, Kurt; Gutierrez, Diego and Sheffer, Alla
    High dynamic range (HDR) imaging provides the capability of handling real world lighting as opposed to the traditional low dynamic range (LDR) which struggles to accurately represent images with higher dynamic range. However, most imaging content is still available only in LDR. This paper presents a method for generating HDR content from LDR content based on deep Convolutional Neural Networks (CNNs) termed ExpandNet. ExpandNet accepts LDR images as input and generates images with an expanded range in an end-to-end fashion. The model attempts to reconstruct missing information that was lost from the original signal due to quantization, clipping, tone mapping or gamma correction. The added information is reconstructed from learned features, as the network is trained in a supervised fashion using a dataset of HDR images. The approach is fully automatic and data driven; it does not require any heuristics or human expertise. ExpandNet uses a multiscale architecture which avoids the use of upsampling layers to improve image quality. The method performs well compared to expansion/inverse tone mapping operators quantitatively on multiple metrics, even for badly exposed inputs.
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    From Faces to Outdoor Light Probes
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Calian, Dan A.; Lalonde, Jean-François; Gotardo, Paulo; Simon, Tomas; Matthews, Iain; Mitchell, Kenny; Gutierrez, Diego and Sheffer, Alla
    Image-based lighting has allowed the creation of photo-realistic computer-generated content. However, it requires the accurate capture of the illumination conditions, a task neither easy nor intuitive, especially to the average digital photography enthusiast. This paper presents an approach to directly estimate an HDR light probe from a single LDR photograph, shot outdoors with a consumer camera, without specialized calibration targets or equipment. Our insight is to use a person's face as an outdoor light probe. To estimate HDR light probes from LDR faces we use an inverse rendering approach which employs data-driven priors to guide the estimation of realistic, HDR lighting. We build compact, realistic representations of outdoor lighting both parametrically and in a data-driven way, by training a deep convolutional autoencoder on a large dataset of HDR sky environment maps. Our approach can recover high-frequency, extremely high dynamic range lighting environments. For quantitative evaluation of lighting estimation accuracy and relighting accuracy, we also contribute a new database of face photographs with corresponding HDR light probes. We show that relighting objects with HDR light probes estimated by our method yields realistic results in a wide variety of settings.
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    Multiple Scattering in Inhomogeneous Participating Media Using Rao-Blackwellization and Control Variates
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Szirmay-Kalos, László; Magdics, Milán; Sbert, Mateu; Gutierrez, Diego and Sheffer, Alla
    Rendering inhomogeneous participating media requires a lot of volume samples since the extinction coefficient needs to be integrated along light paths. Ray marching makes small steps, which is time consuming and leads to biased algorithms. Woodcocklike approaches use analytic sampling and a random rejection scheme guaranteeing that the expectations will be the same as in the original model. These models and the application of control variates for the extinction have been successful to compute transmittance and single scattering but were not fully exploited in multiple scattering simulation. Our paper attacks the multiple scattering problem in heterogeneous media and modifies the light-medium interaction model to allow the use of simple analytic formulae while preserving the correct expected values. The model transformation reduces the variance of the estimates with the help of Rao-Blackwellization and control variates applied both for the extinction coefficient and the incident radiance. Based on the transformed model, efficient Monte Carlo rendering algorithms are obtained.
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    PCPNet: Learning Local Shape Properties from Raw Point Clouds
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Guerrero, Paul; Kleiman, Yanir; Ovsjanikov, Maks; Mitra, Niloy J.; Gutierrez, Diego and Sheffer, Alla
    In this paper, we propose PCPNET, a deep-learning based approach for estimating local 3D shape properties in point clouds. In contrast to the majority of prior techniques that concentrate on global or mid-level attributes, e.g., for shape classification or semantic labeling, we suggest a patch-based learning method, in which a series of local patches at multiple scales around each point is encoded in a structured manner. Our approach is especially well-adapted for estimating local shape properties such as normals (both unoriented and oriented) and curvature from raw point clouds in the presence of strong noise and multi-scale features. Our main contributions include both a novel multi-scale variant of the recently proposed PointNet architecture with emphasis on local shape information, and a series of novel applications in which we demonstrate how learning from training data arising from well-structured triangle meshes, and applying the trained model to noisy point clouds can produce superior results compared to specialized state-of-the-art techniques. Finally, we demonstrate the utility of our approach in the context of shape reconstruction, by showing how it can be used to extract normal orientation information from point clouds.
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    PointProNets: Consolidation of Point Clouds with Convolutional Neural Networks
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Roveri, Riccardo; Öztireli, A. Cengiz; Pandele, Ioana; Gross, Markus; Gutierrez, Diego and Sheffer, Alla
    With the widespread use of 3D acquisition devices, there is an increasing need of consolidating captured noisy and sparse point cloud data for accurate representation of the underlying structures. There are numerous algorithms that rely on a variety of assumptions such as local smoothness to tackle this ill-posed problem. However, such priors lead to loss of important features and geometric detail. Instead, we propose a novel data-driven approach for point cloud consolidation via a convolutional neural network based technique. Our method takes a sparse and noisy point cloud as input, and produces a dense point cloud accurately representing the underlying surface by resolving ambiguities in geometry. The resulting point set can then be used to reconstruct accurate manifold surfaces and estimate surface properties. To achieve this, we propose a generative neural network architecture that can input and output point clouds, unlocking a powerful set of tools from the deep learning literature. We use this architecture to apply convolutional neural networks to local patches of geometry for high quality and efficient point cloud consolidation. This results in significantly more accurate surfaces, as we illustrate with a diversity of examples and comparisons to the state-of-the-art.
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    Terrain Super-resolution through Aerial Imagery and Fully Convolutional Networks
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Argudo, Oscar; Chica, Antonio; Andujar, Carlos; Gutierrez, Diego and Sheffer, Alla
    Despite recent advances in surveying techniques, publicly available Digital Elevation Models (DEMs) of terrains are lowresolution except for selected places on Earth. In this paper we present a new method to turn low-resolution DEMs into plausible and faithful high-resolution terrains. Unlike other approaches for terrain synthesis/amplification (fractal noise, hydraulic and thermal erosion, multi-resolution dictionaries), we benefit from high-resolution aerial images to produce highly-detailed DEMs mimicking the features of the real terrain. We explore different architectures for Fully Convolutional Neural Networks to learn upsampling patterns for DEMs from detailed training sets (high-resolution DEMs and orthophotos), yielding up to one order of magnitude more resolution. Our comparative results show that our method outperforms competing data amplification approaches in terms of elevation accuracy and terrain plausibility.
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    A New Microflake Model With Microscopic Self-shadowing for Accurate Volume Downsampling
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Loubet, Guillaume; Neyret, Fabrice; Gutierrez, Diego and Sheffer, Alla
    Naive linear methods for downsampling high-resolution microflake volumes often produce inaccurate appearance, especially when input voxels are very opaque. Preserving correct appearance at all resolutions requires taking into account maskingshadowing effects that occur between and inside dense input voxels. We introduce a new microflake model whose additional parameters characterize self-shadowing effects at a microscopic scale. We provide an anisotropic self-shadowing function and microflake distributions for which the scattering coefficients and the phase functions of our model have closed-form expressions. We use this model in a new downsampling approach in which scattering parameters are computed from local estimations of self-shadowing probabilities in the input volume. Unlike previous work, our method handles datasets with spatially varying scattering parameters, semi-transparent volumes and datasets with intricate silhouettes. We show that our method generates LoDs with correct transparency and consistent appearance through scales for a wide range of challenging datasets, allowing for huge memory savings and efficient distant rendering without loss of quality.
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    Real-Time Rendering of Wave-Optical Effects on Scratched Surfaces
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Velinov, Zdravko; Werner, Sebastian; Hullin, Matthias B.; Gutierrez, Diego and Sheffer, Alla
    The visual appearance of real-world materials is characterized by surface features across many scales and has received significant attention by the graphics community for decades. Yet, even the most advanced microfacet models have difficulties faithfully recreating materials like snow, sand, brushed metal or hair that feature scale-violating glints and speckles and defy any traditional notion of filtering and level of detail. In this work, we address an important subset of such materials, namely metal and dielectric surfaces that are covered with microscopic scratches, e.g., from polishing processes or surface wear. The appearance of such surfaces features fine-scale spatial detail and iridescent colors caused by diffraction, and has only recently been successfully recreated. We adopt the scratch iridescence model, which is known for plausible results in offline Monte Carlo settings but unsuitable for real-time applications where extensive illumination sampling is prohibitively expensive. In this paper, we introduce an efficient technique for incoherently integrating the contributions of individual scratches, as well as closed-form solutions for modeling spherical and polygonal area light sources, and for the first time bring scratch iridescence within reach of real-time applications.
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    A Versatile Parameterization for Measured Material Manifolds
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Soler, Cyril; Subr, Kartic; Nowrouzezahrai, Derek; Gutierrez, Diego and Sheffer, Alla
    A popular approach for computing photorealistic images of virtual objects requires applying reflectance profiles measured from real surfaces, introducing several challenges: the memory needed to faithfully capture realistic material reflectance is large, the choice of materials is limited to the set of measurements, and image synthesis using the measured data is costly. Typically, this data is either compressed by projecting it onto a subset of its linear principal components or by applying non-linear methods. The former requires many components to faithfully represent the input reflectance, whereas the latter necessitates costly extrapolation algorithms. We learn an underlying, low-dimensional non-linear reflectance manifold amenable to rapid exploration and rendering of real-world materials. We can express interpolated materials as linear combinations of the measured data, despite them lying on an inherently non-linear manifold. This allows us to efficiently interpolate and extrapolate measured BRDFs, and to render directly from the manifold representation. We exploit properties of Gaussian process latent variable models and use our representation for high-performance and offline rendering with interpolated real-world materials.
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    A Physically Consistent Implicit Viscosity Solver for SPH Fluids
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Weiler, Marcel; Koschier, Dan; Brand, Magnus; Bender, Jan; Gutierrez, Diego and Sheffer, Alla
    In this paper, we present a novel physically consistent implicit solver for the simulation of highly viscous fluids using the Smoothed Particle Hydrodynamics (SPH) formalism. Our method is the result of a theoretical and practical in-depth analysis of the most recent implicit SPH solvers for viscous materials. Based on our findings, we developed a list of requirements that are vital to produce a realistic motion of a viscous fluid. These essential requirements include momentum conservation, a physically meaningful behavior under temporal and spatial refinement, the absence of ghost forces induced by spurious viscosities and the ability to reproduce complex physical effects that can be observed in nature. On the basis of several theoretical analyses, quantitative academic comparisons and complex visual experiments we show that none of the recent approaches is able to satisfy all requirements. In contrast, our proposed method meets all demands and therefore produces realistic animations in highly complex scenarios. We demonstrate that our solver outperforms former approaches in terms of physical accuracy and memory consumption while it is comparable in terms of computational performance. In addition to the implicit viscosity solver, we present a method to simulate melting objects. Therefore, we generalize the viscosity model to a spatially varying viscosity field and provide an SPH discretization of the heat equation.
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    Fast Fluid Simulations with Sparse Volumes on the GPU
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Wu, Kui; Truong, Nghia; Yuksel, Cem; Hoetzlein, Rama; Gutierrez, Diego and Sheffer, Alla
    We introduce efficient, large scale fluid simulation on GPU hardware using the fluid-implicit particle (FLIP) method over a sparse hierarchy of grids represented in NVIDIA R GVDB Voxels. Our approach handles tens of millions of particles within a virtually unbounded simulation domain. We describe novel techniques for parallel sparse grid hierarchy construction and fast incremental updates on the GPU for moving particles. In addition, our FLIP technique introduces sparse, work efficient parallel data gathering from particle to voxel, and a matrix-free GPU-based conjugate gradient solver optimized for sparse grids. Our results show that our method can achieve up to an order of magnitude faster simulations on the GPU as compared to FLIP simulations running on the CPU.
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    Extended Narrow Band FLIP for Liquid Simulations
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Sato, Takahiro; Wojtan, Chris; Thuerey, Nils; Igarashi, Takeo; Ando, Ryoichi; Gutierrez, Diego and Sheffer, Alla
    The Fluid Implicit Particle method (FLIP) reduces numerical dissipation by combining particles with grids. To improve performance, the subsequent narrow band FLIP method (NB-FLIP) uses a FLIP-based fluid simulation only near the liquid surface and a traditional grid-based fluid simulation away from the surface. This spatially-limited FLIP simulation significantly reduces the number of particles and alleviates a computational bottleneck. In this paper, we extend the NB-FLIP idea even further, by allowing a simulation to transition between a FLIP-like fluid simulation and a grid-based simulation in arbitrary locations, not just near the surface. This approach leads to even more savings in memory and computation, because we can concentrate the particles only in areas where they are needed. More importantly, this new method allows us to seamlessly transition to smooth implicit surface geometry wherever the particle-based simulation is unnecessary. Consequently, our method leads to a practical algorithm for avoiding the noisy surface artifacts associated with particle-based liquid simulations, while simultaneously maintaining the benefits of a FLIP simulation in regions of dynamic motion.
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    Improved Functional Mappings via Product Preservation
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Nogneng, Dorian; Melzi, Simone; Rodolà, Emanuele; Castellani, Umberto; Bronstein, Michael; Ovsjanikov, Maks; Gutierrez, Diego and Sheffer, Alla
    In this paper, we consider the problem of information transfer across shapes and propose an extension to the widely used functional map representation. Our main observation is that in addition to the vector space structure of the functional spaces, which has been heavily exploited in the functional map framework, the functional algebra (i.e., the ability to take pointwise products of functions) can significantly extend the power of this framework. Equipped with this observation, we show how to improve one of the key applications of functional maps, namely transferring real-valued functions without conversion to point-to-point correspondences. We demonstrate through extensive experiments that by decomposing a given function into a linear combination consisting not only of basis functions but also of their pointwise products, both the representation power and the quality of the function transfer can be improved significantly. Our modification, while computationally simple, allows us to achieve higher transfer accuracy while keeping the size of the basis and the functional map fixed. We also analyze the computational complexity of optimally representing functions through linear combinations of products in a given basis and prove NP-completeness in some general cases. Finally, we argue that the use of function products can have a wide-reaching effect in extending the power of functional maps in a variety of applications, in particular by enabling the transfer of highfrequency functions without changing the representation size or complexity.
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    Visual Attention for Rendered 3D Shapes
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Lavoué, Guillaume; Cordier, Frédéric; Seo, Hyewon; Larabi, Mohamed-Chaker; Gutierrez, Diego and Sheffer, Alla
    Understanding the attentional behavior of the human visual system when visualizing a rendered 3D shape is of great importance for many computer graphics applications. Eye tracking remains the only solution to explore this complex cognitive mechanism. Unfortunately, despite the large number of studies dedicated to images and videos, only a few eye tracking experiments have been conducted using 3D shapes. Thus, potential factors that may influence the human gaze in the specific setting of 3D rendering, are still to be understood. In this work, we conduct two eye-tracking experiments involving 3D shapes, with both static and time-varying camera positions. We propose a method for mapping eye fixations (i.e., where humans gaze) onto the 3D shapes with the aim to produce a benchmark of 3D meshes with fixation density maps, which is publicly available. First, the collected data is used to study the influence of shape, camera position, material and illumination on visual attention. We find that material and lighting have a significant influence on attention, as well as the camera path in the case of dynamic scenes. Then, we compare the performance of four representative state-of-the-art mesh saliency models in predicting ground-truth fixations using two different metrics. We show that, even combined with a center-bias model, the performance of 3D saliency algorithms remains poor at predicting human fixations. To explain their weaknesses, we provide a qualitative analysis of the main factors that attract human attention. We finally provide a comparison of human-eye fixations and Schelling points and show that their correlation is weak.
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    Watch to Edit: Video Retargeting using Gaze
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Rachavarapu, Kranthi Kumar; Kumar, Moneish; Gandhi, Vineet; Subramanian, Ramanathan; Gutierrez, Diego and Sheffer, Alla
    We present a novel approach to optimally retarget videos for varied displays with di ering aspect ratios by preserving salient scene content discovered via eye tracking. Our algorithm performs editing with cut, pan and zoom operations by optimizing the path of a cropping window within the original video while seeking to (i) preserve salient regions, and (ii) adhere to the principles of cinematography. Our approach is (a) content agnostic as the same methodology is employed to re-edit a wide-angle video recording or a close-up movie sequence captured with a static or moving camera, and (b) independent of video length and can in principle re-edit an entire movie in one shot. Our algorithm consists of two steps. The first step employs gaze transition cues to detect time stamps where new cuts are to be introduced in the original video via dynamic programming. A subsequent step optimizes the cropping window path (to create pan and zoom e ects), while accounting for the original and new cuts. The cropping window path is designed to include maximum gaze information, and is composed of piecewise constant, linear and parabolic segments. It is obtained via L(1) regularized convex optimization which ensures a smooth viewing experience. We test our approach on a wide variety of videos and demonstrate significant improvement over the state-of-the-art, both in terms of computational complexity and qualitative aspects. A study performed with 16 users confirms that our approach results in a superior viewing experience as compared to gaze driven re-editing [JSSH15] and letterboxing methods, especially for wide-angle static camera recordings.
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    GazeDirector: Fully Articulated Eye Gaze Redirection in Video
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Wood, Erroll; Baltrušaitis, Tadas; Morency, Louis-Philippe; Robinson, Peter; Bulling, Andreas; Gutierrez, Diego and Sheffer, Alla
    We present GazeDirector, a new approach for eye gaze redirection that uses model-fitting. Our method first tracks the eyes by fitting a multi-part eye region model to video frames using analysis-by-synthesis, thereby recovering eye region shape, texture, pose, and gaze simultaneously. It then redirects gaze by 1) warping the eyelids from the original image using a model-derived flow field, and 2) rendering and compositing synthesized 3D eyeballs onto the output image in a photorealistic manner. GazeDirector allows us to change where people are looking without person-specific training data, and with full articulation, i.e. we can precisely specify new gaze directions in 3D. Quantitatively, we evaluate both model-fitting and gaze synthesis, with experiments for gaze estimation and redirection on the Columbia gaze dataset. Qualitatively, we compare GazeDirector against recent work on gaze redirection, showing better results especially for large redirection angles. Finally, we demonstrate gaze redirection on YouTube videos by introducing new 3D gaze targets and by manipulating visual behavior.
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    Efficient BVH-based Collision Detection Scheme with Ordering and Restructuring
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Wang, Xinlei; Tang, Min; Manocha, Dinesh; Tong, Ruofeng; Gutierrez, Diego and Sheffer, Alla
    Bounding volume hierarchy (BVH) has been widely adopted as the acceleration structure in broad-phase collision detection. Previous state-of-the-art BVH-based collision detection approaches exploited the spatio-temporal coherence of simulations by maintaining a bounding volume test tree (BVTT) front. A major drawback of these algorithms is that large deformations in the scenes decrease culling efficiency and slow down collision queries. Moreover, for front-based methods, the inefficient caching on GPU caused by the arbitrary layout of BVH and BVTT front nodes becomes a critical performance issue. We present a fast and robust BVH-based collision detection scheme on GPU that addresses the above problems by ordering and restructuring BVHs and BVTT fronts. Our techniques are based on the use of histogram sort and an auxiliary structure BVTT front log, through which we analyze the dynamic status of BVTT front and BVH quality. Our approach efficiently handles inter- and intra-object collisions and performs especially well in simulations where there is considerable spatio-temporal coherence. The benchmark results demonstrate that our approach is significantly faster than the previous BVH-based method, and also outperforms other state-of-the-art spatial subdivision schemes in terms of speed.
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    Fast Penetration Volume for Rigid Bodies
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Nirel, Dan; Lischinski, Dani; Gutierrez, Diego and Sheffer, Alla
    Handling collisions among a large number of bodies can be a performance bottleneck in video games and many other real-time applications. We present a new framework for detecting and resolving collisions using the penetration volume as an interpenetration measure. Given two non-convex polyhedral bodies, a new sampling paradigm locates their near-contact configurations in advance, and stores associated contact information in a compact database. At runtime, we retrieve a given configuration's nearest neighbors. By taking advantage of the penetration volume's continuity, cheap geometric methods can use the neighbors to estimate contact information as well as a translational gradient. This results in an extremely fast, geometry-independent, and trivially parallelizable computation, which constitutes the first global volume-based collision resolution. When processing multiple collisions simultaneously on a 4-core processor, the average running cost is as low as 5 μs. Furthermore, no additional proximity or contact-regions queries are required. These results are orders of magnitude faster than previous penetration volume approaches.
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    Packable Springs
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Wolff, Katja; Poranne, Roi; Glauser, Oliver; Sorkine-Hornung, Olga; Gutierrez, Diego and Sheffer, Alla
    Laser cutting is an appealing fabrication process due to the low cost of materials and extremely fast fabrication. However, the design space afforded by laser cutting is limited, since only flat panels can be cut. Previous methods for manufacturing from flat sheets usually roughly approximate 3D objects by polyhedrons or cross sections. Computational design methods for connecting, interlocking, or folding several laser cut panels have been introduced; to obtain a good approximation, these methods require numerous parts and long assembly times. In this paper, we propose a radically different approach: Our approximation is based on cutting thin, planar spirals out of flat panels. When such spirals are pulled apart, they take on the shape of a 3D spring whose contours are similar to the input object. We devise an optimization problem that aims to minimize the number of required parts, thus reducing costs and fabrication time, while at the same time ensuring that the resulting spring mimics the shape of the original object. In addition to rapid fabrication and assembly, our method enables compact packaging and storage as flat parts. We also demonstrate its use for creating armatures for sculptures and moulds for filling, with potential applications in architecture or construction.
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    String Art: Towards Computational Fabrication of String Images
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Birsak, Michael; Rist, Florian; Wonka, Peter; Musialski, Przemyslaw; Gutierrez, Diego and Sheffer, Alla
    In this paper we propose a novel method for the automatic computation and digital fabrication of artistic string images. String art is a technique used by artists for the creation of abstracted images which are composed of straight lines of strings tensioned between pins distributed on a frame. Together the strings fuse to a perceptible image. Traditionally, artists craft such images manually in a highly sophisticated and tedious design process. To achieve this goal fully automatically we propose a computational setup driven by a discrete optimization algorithm which takes an ordinary picture as input and converts it into a connected graph of strings that tries to reassemble the input image best possibly. Furthermore, we propose a hardware setup for automatic digital fabrication of these images using an industrial robot that spans the strings. Finally, we demonstrate the applicability of our approach by generating and fabricating a set of real string art images.
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    Watercolor Woodblock Printing with Image Analysis
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Panotopoulou, Athina; Paris, Sylvain; Whiting, Emily; Gutierrez, Diego and Sheffer, Alla
    Watercolor paintings have a unique look that mixes subtle color gradients and sophisticated diffusion patterns. This makes them immediately recognizable and gives them a unique appeal. Creating such paintings requires advanced skills that are beyond the reach of most people. Even for trained artists, producing several copies of a painting is a tedious task. One can resort to scanning an existing painting and printing replicas, but these are all identical and have lost an essential characteristic of a painting, its uniqueness. We address these two issues with a technique to fabricate woodblocks that we later use to create watercolor prints. The woodblocks can be reused to produce multiple copies but each print is unique due to the physical process that we introduce. We also design an image processing pipeline that helps users to create the woodblocks and describe a protocol that produces prints by carefully controlling the interplay between the paper, ink pigments, and water so that the final piece depicts the desired scene while exhibiting the distinctive features of watercolor. Our technique enables anyone with the resources to produce watercolor prints.
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    Real-time Locomotion Controller using an Inverted-Pendulum-based Abstract Model
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Hwang, Jaepyung; Kim, Jongmin; Suh, Il Hong; Kwon, Taesoo; Gutierrez, Diego and Sheffer, Alla
    In this paper, we propose a novel motion controller for the online generation of natural character locomotion that adapts to new situations such as changing user control or applying external forces. This controller continuously estimates the next footstep while walking and running, and automatically switches the stepping strategy based on situational changes. To develop the controller, we devise a new physical model called an inverted-pendulum-based abstract model (IPAM). The proposed abstract model represents high-dimensional character motions, inheriting the naturalness of captured motions by estimating the appropriate footstep location, speed and switching time at every frame. The estimation is achieved by a deep learning based regressor that extracts important features in captured motions. To validate the proposed controller, we train the model using captured motions of a human stopping, walking, and running in a limited space. Then, the motion controller generates humanlike locomotion with continuously varying speeds, transitions between walking and running, and collision response strategies in a cluttered space in real time.
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    Self-similarity Analysis for Motion Capture Cleaning
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Aristidou, Andreas; Cohen-Or, Daniel; Hodgins, Jessica K.; Shamir, Ariel; Gutierrez, Diego and Sheffer, Alla
    Motion capture sequences may contain erroneous data, especially when the motion is complex or performers are interacting closely and occlusions are frequent. Common practice is to have specialists visually detect the abnormalities and fix them manually. In this paper, we present a method to automatically analyze and fix motion capture sequences by using self-similarity analysis. The premise of this work is that human motion data has a high-degree of self-similarity. Therefore, given enough motion data, erroneous motions are distinct when compared to other motions. We utilize motion-words that consist of short sequences of transformations of groups of joints around a given motion frame. We search for the K-nearest neighbors (KNN) set of each word using dynamic time warping and use it to detect and fix erroneous motions automatically. We demonstrate the effectiveness of our method in various examples, and evaluate by comparing to alternative methods and to manual cleaning.
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    Aura Mesh: Motion Retargeting to Preserve the Spatial Relationships between Skinned Characters
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Jin, Taeil; Kim, Meekyoung; Lee, Sung-Hee; Gutierrez, Diego and Sheffer, Alla
    Applying motion-capture data to multi-person interaction between virtual characters is challenging because one needs to preserve the interaction semantics while also satisfying the general requirements of motion retargeting, such as preventing penetration and preserving naturalness. An efficient means of representing interaction semantics is by defining the spatial relationships between the body parts of characters. However, existing methods consider only the character skeleton and thus are not suitable for capturing skin-level spatial relationships. This paper proposes a novel method for retargeting interaction motions with respect to character skins. Specifically, we introduce the aura mesh, which is a volumetric mesh that surrounds a character's skin. The spatial relationships between two characters are computed from the overlap of the skin mesh of one character and the aura mesh of the other, and then the interaction motion retargeting is achieved by preserving the spatial relationships as much as possible while satisfying other constraints. We show the effectiveness of our method through a number of experiments.
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    Flexible Live-Wire: Image Segmentation with Floating Anchors
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Summa, Brian; Faraj, Noura; Licorish, Cody; Pascucci, Valerio; Gutierrez, Diego and Sheffer, Alla
    We introduce Flexible Live-Wire, a generalization of the Live-Wire interactive segmentation technique with floating anchors. In our approach, the user input for Live-Wire is no longer limited to the setting of pixel-level anchor nodes, but can use more general anchor sets. These sets can be of any dimension, size, or connectedness. The generality of the approach allows the design of a number of user interactions while providing the same functionality as the traditional Live-Wire. In particular, we experiment with this new flexibility by designing four novel Live-Wire interactions based on specific primitives: paint, pinch, probable, and pick anchors. These interactions are only a subset of the possibilities enabled by our generalization. Moreover, we discuss the computational aspects of this approach and provide practical solutions to alleviate any additional overhead. Finally, we illustrate our approach and new interactions through several example segmentations.
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    Semantic Segmentation for Line Drawing Vectorization Using Neural Networks
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kim, Byungsoo; Wang, Oliver; Öztireli, A. Cengiz; Gross, Markus; Gutierrez, Diego and Sheffer, Alla
    In this work, we present a method to vectorize raster images of line art. Inverting the rasterization procedure is inherently ill-conditioned, as there exist many possible vector images that could yield the same raster image. However, not all of these vector images are equally useful to the user, especially if performing further edits is desired. We therefore define the problem of computing an instance segmentation of the most likely set of paths that could have created the raster image. Once the segmentation is computed, we use existing vectorization approaches to vectorize each path, and then combine all paths into the final output vector image. To determine which set of paths is most likely, we train a pair of neural networks to provide semantic clues that help resolve ambiguities at intersection and overlap regions. These predictions are made considering the full context of the image, and are then globally combined by solving a Markov Random Field (MRF). We demonstrate the flexibility of our method by generating results on character datasets, a synthetic random line dataset, and a dataset composed of human drawn sketches. For all cases, our system accurately recovers paths that adhere to the semantics of the drawings.
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    Sequences with Low-Discrepancy Blue-Noise 2-D Projections
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Perrier, Hélène; Coeurjolly, David; Xie, Feng; Pharr, Matt; Hanrahan, Pat; Ostromoukhov, Victor; Gutierrez, Diego and Sheffer, Alla
    Distributions of samples play a very important role in rendering, affecting variance, bias and aliasing in Monte-Carlo and Quasi-Monte Carlo evaluation of the rendering equation. In this paper, we propose an original sampler which inherits many important features of classical low-discrepancy sequences (LDS): a high degree of uniformity of the achieved distribution of samples, computational efficiency and progressive sampling capability. At the same time, we purposely tailor our sampler in order to improve its spectral characteristics, which in turn play a crucial role in variance reduction, anti-aliasing and improving visual appearance of rendering. Our sampler can efficiently generate sequences of multidimensional points, whose power spectra approach so-called Blue-Noise (BN) spectral property while preserving low discrepancy (LD) in certain 2-D projections. In our tile-based approach, we perform permutations on subsets of the original Sobol LDS. In a large space of all possible permutations, we select those which better approach the target BN property, using pair-correlation statistics. We pre-calculate such ''good'' permutations for each possible Sobol pattern, and store them in a lookup table efficiently accessible in runtime. We provide a complete and rigorous proof that such permutations preserve dyadic partitioning and thus the LDS properties of the point set in 2-D projections. Our construction is computationally efficient, has a relatively low memory footprint and supports adaptive sampling. We validate our method by performing spectral/discrepancy/aliasing analysis of the achieved distributions, and provide variance analysis for several target integrands of theoretical and practical interest.
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    Hair Modeling and Simulation by Style
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Jung, Seunghwan; Lee, Sung-Hee; Gutierrez, Diego and Sheffer, Alla
    As the deformation behaviors of hair strands vary greatly depending on the hairstyle, the computational cost and accuracy of hair movement simulations can be significantly improved by applying simulation methods specific to a certain style. This paper makes two contributions with regard to the simulation of various hair styles. First, we propose a novel method to reconstruct simulatable hair strands from hair meshes created by artists. Manually created hair meshes consist of numerous mesh patches, and the strand reconstruction process is challenged by the absence of connectivity information among the patches for the same strand and the omission of hidden parts of strands due to the manual creation process. To this end, we develop a two-stage spectral clustering method for estimating the degree of connectivity among patches and a strand-growing method that preserves hairstyles. Next, we develop a hairstyle classification method for style-specific simulations. In particular, we propose a set of features for efficient classifications and show that classifiers trained with the proposed features have higher accuracy than those trained with naive features. Our method applies efficient simulation methods according to the hairstyle without specific user input, and thus is favorable for real-time simulation.
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    Practical Radiometric Compensation for Projection Display on Textured Surfaces using a Multidimensional Model
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Li, Yuqi; Majumder, Aditi; Gopi, Meenakshisundaram; Wang, Chong; Zhao, Jieyu; Gutierrez, Diego and Sheffer, Alla
    Radiometric compensation methods remove the effect of the underlying spatially varying surface reflectance of the texture when projecting on textured surfaces. All prior work sample the surface reflectance dependent radiometric transfer function from the projector to the camera at every pixel that requires the camera to observe tens or hundreds of images projected by the projector. In this paper, we cast the radiometric compensation problem as a sampling and reconstruction of multi-dimensional radiometric transfer function that models the color transfer function from the projector to an observing camera and the surface reflectance in a unified manner. Such a multi-dimensional representation makes no assumption about linearity of the projector to camera color transfer function and can therefore handle projectors with non-linear color transfer functions(e.g. DLP, LCOS, LED-based or laser-based).We show that with a well-curated sampling of this multi-dimensional function, achieved by exploiting the following key properties, is adequate for its accurate representation: (a) the spectral reflectance of most real-world materials are smooth and can be well-represented using a lower-dimension function; (b) the reflectance properties of the underlying texture have strong redundancies –- for example, multiple pixels or even regions can have similar surface reflectance; (c) the color transfer function from the projector to camera have strong input coherence. The proposed sampling allows us to reduce the number of projected images that needs to be observed by a camera by up to two orders of magnitude, the minimum being only two. We then present a new multi-dimensional scattered data interpolation technique to reconstruct the radiometric transfer function at a high spatial density (i.e. at every pixel) to compute the compensation image. We show that the accuracy of our interpolation technique is higher than any existing methods.
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    Single-image Tomography: 3D Volumes from 2D Cranial X-Rays
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Henzler, Philipp; Rasche, Volker; Ropinski, Timo; Ritschel, Tobias; Gutierrez, Diego and Sheffer, Alla
    As many different 3D volumes could produce the same 2D x-ray image, inverting this process is challenging. We show that recent deep learning-based convolutional neural networks can solve this task. As the main challenge in learning is the sheer amount of data created when extending the 2D image into a 3D volume, we suggest firstly to learn a coarse, fixed-resolution volume which is then fused in a second step with the input x-ray into a high-resolution volume. To train and validate our approach we introduce a new dataset that comprises of close to half a million computer-simulated 2D x-ray images of 3D volumes scanned from 175 mammalian species. Future applications of our approach include stereoscopic rendering of legacy x-ray images, re-rendering of x-rays including changes of illumination, view pose or geometry. Our evaluation includes comparison to previous tomography work, previous learning methods using our data, a user study and application to a set of real x-rays.
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    Deep Joint Design of Color Filter Arrays and Demosaicing
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Henz, Bernardo; Gastal, Eduardo S. L.; Oliveira, Manuel M.; Gutierrez, Diego and Sheffer, Alla
    We present a convolutional neural network architecture for performing joint design of color filter array (CFA) patterns and demosaicing. Our generic model allows the training of CFAs of arbitrary sizes, optimizing each color filter over the entire RGB color space. The patterns and algorithms produced by our method provide high-quality color reconstructions. We demonstrate the effectiveness of our approach by showing that its results achieve higher PSNR than the ones obtained with state-of-the-art techniques on all standard demosaicing datasets, both for noise-free and noisy scenarios. Our method can also be used to obtain demosaicing strategies for pre-defined CFAs, such as the Bayer pattern, for which our results also surpass even the demosaicing algorithms specifically designed for such a pattern.
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    Example-based Authoring of Procedural Modeling Programs with Structural and Continuous Variability
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Ritchie, Daniel; Jobalia, Sarah; Thomas, Anna; Gutierrez, Diego and Sheffer, Alla
    Procedural models are a powerful tool for quickly creating a variety of computer graphics content. However, authoring them is challenging, requiring both programming and artistic expertise. In this paper, we present a method for learning procedural models from a small number of example objects. We focus on the modular design setting, where objects are constructed from a common library of parts. Our procedural representation is a probabilistic program that models both the discrete, hierarchical structure of the examples as well as the continuous variability in their spatial arrangements of parts. We develop an algorithm for learning such programs from examples, using combinatorial search over program structures and variational inference to estimate continuous program parameters. We evaluate our method by demonstrating its ability to learn programs from examples of ornamental designs, spaceships, space stations, and castles. Experiments suggest that our learned programs can reliably generate a variety of new objects that are perceptually indistinguishable from hand-crafted examples.
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    Procedural Modeling of a Building from a Single Image
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Nishida, Gen; Bousseau, Adrien; Aliaga, Daniel G.; Gutierrez, Diego and Sheffer, Alla
    Creating a virtual city is demanded for computer games, movies, and urban planning, but it takes a lot of time to create numerous 3D building models. Procedural modeling has become popular in recent years to overcome this issue, but creating a grammar to get a desired output is difficult and time consuming even for expert users. In this paper, we present an interactive tool that allows users to automatically generate such a grammar from a single image of a building. The user selects a photograph and highlights the silhouette of the target building as input to our method. Our pipeline automatically generates the building components, from large-scale building mass to fine-scale windows and doors geometry. Each stage of our pipeline combines convolutional neural networks (CNNs) and optimization to select and parameterize procedural grammars that reproduce the building elements of the picture. In the first stage, our method jointly estimates camera parameters and building mass shape. Once known, the building mass enables the rectification of the façades, which are given as input to the second stage that recovers the façade layout. This layout allows us to extract individual windows and doors that are subsequently fed to the last stage of the pipeline that selects procedural grammars for windows and doors. Finally, the grammars are combined to generate a complete procedural building as output. We devise a common methodology to make each stage of this pipeline tractable. This methodology consists in simplifying the input image to match the visual appearance of synthetic training data, and in using optimization to refine the parameters estimated by CNNs. We used our method to generate a variety of procedural models of buildings from existing photographs.
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    Procedural Cloudscapes
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Webanck, Antoine; Cortial, Yann; Guérin, Eric; Galin, Eric; Gutierrez, Diego and Sheffer, Alla
    We present a phenomenological approach for modeling and animating cloudscapes. We propose a compact procedural model for representing the different types of cloud over a range of altitudes. We define primitive-based field functions that allow the user to control and author the cloud cover over large distances easily. Our approach allows us to animate cloudscapes by morphing: instead of simulating the evolution of clouds using a physically-based simulation, we compute the movement of clouds using key-frame interpolation and tackle the morphing problem as an Optimal Transport problem. The trajectories of the cloud cover primitives are generated by solving an Anisotropic Shortest Path problem with a cost function that takes into account the elevation of the terrain and the parameters of the wind field.
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    Approximate Program Smoothing Using Mean-Variance Statistics, with Application to Procedural Shader Bandlimiting
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Yang, Yuting; Barnes, Connelly; Gutierrez, Diego and Sheffer, Alla
    We introduce a general method to approximate the convolution of a program with a Gaussian kernel. This results in the program being smoothed. Our compiler framework models intermediate values in the program as random variables, by using mean and variance statistics. We decompose the input program into atomic parts and relate the statistics of the different parts of the smoothed program. We give several approximate smoothing rules that can be used for the parts of the program. These include an improved variant of Dorn et al. [DBLW15], a novel adaptive Gaussian approximation, Monte Carlo sampling, and compactly supported kernels. Our adaptive Gaussian approximation handles multivariate Gaussian distributed inputs, gives exact results for a larger class of programs than previous work, and is accurate to the second order in the standard deviation of the kernel for programs with certain analytic properties. Because each expression in the program can have multiple approximation choices, we use a genetic search to automatically select the best approximations. We apply this framework to the problem of automatically bandlimiting procedural shader programs. We evaluate our method on a variety of geometries and complex shaders, including shaders with parallax mapping, animation, and spatially varying statistics. The resulting smoothed shader programs outperform previous approaches both numerically and aesthetically.
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    Fast Catmull-Rom Spline Interpolation for High-Quality Texture Sampling
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Csébfalvi, Balázs; Gutierrez, Diego and Sheffer, Alla
    It is well known that cubic texture filtering can be efficiently implemented on the GPU by using a method published by Sigg and Hadwiger [SH05], which simplifies the evaluation to a linear combination of linear texture fetches. However, their method cannot be directly applied if the filter kernel takes also negative values like the popular Catmull-Rom spline, for example. In this paper, we propose a modified algorithm that is able to handle also the negative weights. Therefore, using our method, the Catmull-Rom spline interpolation can also be evaluated in one, two, and three dimensions by taking two, four, and eight linear texture fetches, respectively.
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    Parallel Reinsertion for Bounding Volume Hierarchy Optimization
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Meister, Daniel; Bittner, Jiří; Gutierrez, Diego and Sheffer, Alla
    We present a novel highly parallel method for optimizing bounding volume hierarchies (BVH) targeting contemporary GPU architectures. The core of our method is based on the insertion-based BVH optimization that is known to achieve excellent results in terms of the SAH cost. The original algorithm is, however, inherently sequential: no efficient parallel version of the method exists, which limits its practical utility. We reformulate the algorithm while exploiting the observation that there is no need to remove the nodes from the BVH prior to finding their optimized positions in the tree. We can search for the optimized positions for all nodes in parallel while simultaneously tracking the corresponding SAH cost reduction.We update in parallel all nodes for which better position was found while efficiently handling potential conflicts during these updates. We implemented our algorithm in CUDA and evaluated the resulting BVH in the context of the GPU ray tracing. The results indicate that the method is able to achieve the best ray traversal performance among the state of the art GPU-based BVH construction methods.
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    Motion Sickness Simulation Based on Sensorimotor Control
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Hu, Chen-Hui; Lin, Wen-Chieh; Gutierrez, Diego and Sheffer, Alla
    Sensorimotor control is an essential mechanism for human motions, from involuntary reflex actions to intentional motor skill learning, such as walking, jumping, and swimming. Humans perform various motions according to different task goals and physiological sensory perception; however, most existing computational approaches for motion simulation and generation rarely consider the effects of human perception. The assumption of perfect perception (i.e., no sensory errors) of existing approaches restricts the generated motion types and makes dynamical reactions less realistic. We propose a general framework for sensorimotor control, integrating a balance controller and a vestibular model, to generate perception-aware motions. By exploiting simulated perception, more natural responses that are closer to human reactions can be generated. For example, motion sickness caused by the impairments in the function of the vestibular system induces postural instability and body sway. Our approach generates physically correct motions and reasonable reactions to external stimuli since the spatial orientation estimation by the vestibular system is essential to preserve balance. We evaluate our framework by demonstrating standing balance on a rotational platform with different angular speeds and duration. The generated motions show that either faster angular speeds or longer rotational duration cause more severe motion sickness. Our results demonstrate that sensorimotor control, integrating human perception and physically-based control, offers considerable potential for providing more human-like behaviors, especially for perceptual illusions of human beings, including visual, proprioceptive, and tactile sensations.
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    Controllable Dendritic Crystal Simulation Using Orientation Field
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Ren, Bo; Huang, Jiahui; Lin, Ming C.; Hu, Shi-Min; Gutierrez, Diego and Sheffer, Alla
    Real world dendritic growths show charming structures by their exquisite balance between the symmetry and randomness in the crystal formation. Other than the variety in the natural crystals, richer visual appearance of crystals can benefit from artificially controlling of the crystal growth on its growing directions and shapes. In this paper, by introducing one extra dimension of freedom, i.e. the orientation field, into the simulation, we propose an efficient algorithm for dendritic crystal simulation that is able to reproduce arbitrary symmetry patterns with different levels of asymmetry breaking effect on general grids or meshes, including spreading on curved surfaces and growth in 3D. Flexible artistic control is also enabled in a unified manner by exploiting and guiding the orientation field in the visual simulation. We show the effectiveness of our approach by various demonstrations of simulation results.
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    Interactive Generation of Time-evolving, Snow-Covered Landscapes with Avalanches
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Cordonnier, Guillaume; Ecormier, Pierre; Galin, Eric; Gain, James; Benes, Bedrich; Cani, Marie-Paule; Gutierrez, Diego and Sheffer, Alla
    We introduce a novel method for interactive generation of visually consistent, snow-covered landscapes and provide control of their dynamic evolution over time. Our main contribution is the real-time phenomenological simulation of avalanches and other user-guided events, such as tracks left by Nordic skiing, which can be applied to interactively sculpt the landscape. The terrain is modeled as a height field with additional layers for stable, compacted, unstable, and powdery snow, which behave in combination as a semi-viscous fluid. We incorporate the impact of several phenomena, including sunlight, temperature, prevailing wind direction, and skiing activities. The snow evolution includes snow-melt and snow-drift, which a ect stability of the snow mass and the probability of avalanches. A user can shape landscapes and their evolution either with a variety of interactive brushes, or by prescribing events along a winter season time-line. Our optimized GPU-implementation allows interactive updates of snow type and depth across a large (10 10km) terrain, including real-time avalanches, making this suitable for visual assets in computer games. We evaluate our method through perceptual comparison against exiting methods and real snow-depth data.
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    MIQP-based Layout Design for Building Interiors
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Wu, Wenming; Fan, Lubin; Liu, Ligang; Wonka, Peter; Gutierrez, Diego and Sheffer, Alla
    We propose a hierarchical framework for the generation of building interiors. Our solution is based on a mixed integer quadratic programming (MIQP) formulation. We parametrize a layout by polygons that are further decomposed into small rectangles. We identify important high-level constraints, such as room size, room position, room adjacency, and the outline of the building, and formulate them in a way that is compatible with MIQP and the problem parametrization. We also propose a hierarchical framework to improve the scalability of the approach. We demonstrate that our algorithm can be used for residential building layouts and can be scaled up to large layouts such as office buildings, shopping malls, and supermarkets. We show that our method is faster by multiple orders of magnitude than previous methods.