37-Issue 7

Permanent URI for this collection

Pacific Graphics 2018 - Symposium Proceedings
Hong Kong, China
8-11 October, 2018
(for Short Papers and Posters see PG 2018 - Short Papers and Posters)
Registration and Reconstruction
Online Global Non-rigid Registration for 3D Object Reconstruction Using Consumer-level Depth Cameras
Jiamin Xu, Weiwei Xu, Yin Yang, Zhigang Deng, and Hujun Bao
Biorthogonal Wavelet Surface Reconstruction Using Partial Integrations
Xiaohua Ren, Luan Lyu, Xiaowei He, Wei Cao, Zhixin Yang, Bin Sheng, Yanci Zhang, and Enhua Wu
Semantic Reconstruction: Reconstruction of Semantically Segmented 3D Meshes via Volumetric Semantic Fusion
Junho Jeon, Jinwoong Jung, Jungeon Kim, and Seungyong Lee
Lighting and Ray Tracing
Light Optimization for Detail Highlighting
Anastasios Gkaravelis and Georgios Papaioannou
Directing the Photography: Combining Cinematic Rules, Indirect Light Controls and Lighting-by-Example
Quentin Galvane, Christophe Lino, Marc Christie, and Rémi Cozot
Fast Global Illumination with Discrete Stochastic Microfacets Using a Filterable Model
Beibei Wang, Lu Wang, and Nicolas Holzschuch
Feature Generation for Adaptive Gradient-Domain Path Tracing
Jonghee Back, Sung-Eui Yoon, and Bochang Moon
Geometry Processing
Mumford-Shah Mesh Processing using the Ambrosio-Tortorelli Functional
Nicolas Bonneel, David Coeurjolly, Pierre Gueth, and Jacques-Olivier Lachaud
Ellipsoid Packing Structures on Freeform Surfaces
Qun-Ce Xu, Bailin Deng, and Yong-Liang Yang
Style Transfer
Controlling Stroke Size in Fast Style Transfer with Recurrent Convolutional Neural Network
Lingchen Yang, Lumin Yang, Mingbo Zhao, and Youyi Zheng
FashionGAN: Display your fashion design using Conditional Generative Adversarial Nets
Yi Rui Cui, Qi Liu, Cheng Ying Gao, and Zhuo Su
Animation
Reformulating Hyperelastic Materials with Peridynamic Modeling
Liyou Xu, Xiaowei He, Wei Chen, Sheng Li, and Guoping Wang
Parallel Multigrid for Nonlinear Cloth Simulation
Zhendong Wang, Longhua Wu, Marco Fratarcangeli, Min Tang, and Huamin Wang
Few-shot Learning of Homogeneous Human Locomotion Styles
Ian Mason, Sebastian Starke, He Zhang, Hakan Bilen, and Taku Komura
Mesh Denoising
Non-Local Low-Rank Normal Filtering for Mesh Denoising
Xianzhi Li, Lei Zhu, Chi-Wing Fu, and Pheng-Ann Heng
Sketch-based Interfaces
Reconstructing Flowers from Sketches
Cédric Bobenrieth, Hyewon Seo, Frédéric Cordier, and Arash Habibi
Dynamic Deep Octree for High-resolution Volumetric Painting in Virtual Reality
Yeojin Kim, Byungmoon Kim, and Young J. Kim
Uncut Aerial Video via a Single Sketch
Hao Yang, Ke Xie, Shengqiu Huang, and Hui Huang
Appearance and Illumination
Single Image Surface Appearance Modeling with Self-augmented CNNs and Inexact Supervision
Wenjie Ye, Xiao Li, Yue Dong, Pieter Peers, and Xin Tong
Learning Scene Illumination by Pairwise Photos from Rear and Front Mobile Cameras
Dachuan Cheng, Jian Shi, Yanyun Chen, Xiaoming Deng, and Xiaopeng Zhang
A Practical Approach to Physically-Based Reproduction of Diffusive Cosmetics
Goanghun Kim and Hyeong-Seok Ko
Parameterization and Surface Texture
Piecewise Linear Mapping Optimization Based on the Complex View
Björn Golla, Hans-Peter Seidel, and Renjie Chen
A New Uniform Format for 360 VR Videos
Juan Guo, Qikai K. Pei, Guilong L. Ma, Li Liu, and Xinyu Y. Zhang
Instant Stippling on 3D Scenes
Lei Ma, Jianwei Guo, Dong-Ming Yan, Hanqiu Sun, and Yanyun Chen
Towards Better Quality of Images/Videos
Deep Video Stabilization Using Adversarial Networks
Sen-Zhe Xu, Jun Hu, Miao Wang, Tai-Jiang Mu, and Shi-Min Hu
Defocus and Motion Blur Detection with Deep Contextual Features
Beomseok Kim, Hyeongseok Son, Seong-Jin Park, Sunghyun Cho, and Seungyong Lee
Generative Adversarial Image Super-Resolution Through Deep Dense Skip Connections
Xiaobin Zhu, Zhuangzi Li, Xiaoyu Zhang, Haisheng Li, Ziyu Xue, and Lei Wang
Skeleton and Deformation
DMAT: Deformable Medial Axis Transform for Animated Mesh Approximation
Baorong Yang, Junfeng Yao, and Xiaohu Guo
Improved Use of LOP for Curve Skeleton Extraction
Lei Li and Wencheng Wang
Skeletex: Skeleton-texture Co-representation for Topology-driven Real-time Interchange and Manipulation of Surface Regions
Martin Madaras, Adam Riecický, Michal Mesároš, Martin Stuchlík, and Michal Piovarči
3D Modeling
Automatic Mechanism Modeling from a Single Image with CNNs
Minmin Lin, Tianjia Shao, Youyi Zheng, Zhong Ren, Yanlin Weng, and Yin Yang
Sit & Relax: Interactive Design of Body-Supporting Surfaces
Kurt Leimer, Michael Birsak, Florian Rist, and Przemyslaw Musialski
Shape and Pose Estimation for Closely Interacting Persons Using Multi-view Images
Kun Li, Nianhong Jiao, Yebin Liu, Yangang Wang, and Jingyu Yang
2D and 2.5D Design
Local and Hierarchical Refinement for Subdivision Gradient Meshes
Teun W. Verstraaten and Jiri Kosinka
Modeling Fonts in Context: Font Prediction on Web Designs
Nanxuan Zhao, Ying Cao, and Rynson W. H. Lau
Image Decomposition and Recoloring
Decomposing Images into Layers with Advanced Color Blending
Yuki Koyama and Masataka Goto
Unsupervised Deep Single-Image Intrinsic Decomposition using Illumination-Varying Image Sequences
Louis Lettry, Kenneth Vanhoey, and Luc Van Gool
Translucent Image Recoloring through Homography Estimation
Yifei Huang, Changbo Wang, and Chenhui Li
Binocular Tone Mapping with Improved Overall Contrast and Local Details
Zhuming Zhang, Xinghong Hu, Xueting Liu, and Tien-Tsin Wong
Visualization and GPU
GPU-based Polynomial Finite Element Matrix Assembly for Simplex Meshes
Johannes Sebastian Mueller-Roemer and André Stork
Subdivision Surfaces
Subdivision Schemes With Optimal Bounded Curvature Near Extraordinary Vertices
Yue Ma and Weiyin Ma
Curvature Continuity Conditions Between Adjacent Toric Surface Patches
Lanyin Sun and Chungang Zhu

BibTeX (37-Issue 7)
                
@article{
10.1111:cgf.13542,
journal = {Computer Graphics Forum}, title = {{
Online Global Non-rigid Registration for 3D Object Reconstruction Using Consumer-level Depth Cameras}},
author = {
Xu, Jiamin
and
Xu, Weiwei
and
Yang, Yin
and
Deng, Zhigang
and
Bao, Hujun
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13542}
}
                
@article{
10.1111:cgf.13543,
journal = {Computer Graphics Forum}, title = {{
Biorthogonal Wavelet Surface Reconstruction Using Partial Integrations}},
author = {
Ren, Xiaohua
and
Lyu, Luan
and
He, Xiaowei
and
Cao, Wei
and
Yang, Zhixin
and
Sheng, Bin
and
Zhang, Yanci
and
Wu, Enhua
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13543}
}
                
@article{
10.1111:cgf.13544,
journal = {Computer Graphics Forum}, title = {{
Semantic Reconstruction: Reconstruction of Semantically Segmented 3D Meshes via Volumetric Semantic Fusion}},
author = {
Jeon, Junho
and
Jung, Jinwoong
and
Kim, Jungeon
and
Lee, Seungyong
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13544}
}
                
@article{
10.1111:cgf.13545,
journal = {Computer Graphics Forum}, title = {{
Light Optimization for Detail Highlighting}},
author = {
Gkaravelis, Anastasios
and
Papaioannou, Georgios
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13545}
}
                
@article{
10.1111:cgf.13546,
journal = {Computer Graphics Forum}, title = {{
Directing the Photography: Combining Cinematic Rules, Indirect Light Controls and Lighting-by-Example}},
author = {
Galvane, Quentin
and
Lino, Christophe
and
Christie, Marc
and
Cozot, Rémi
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13546}
}
                
@article{
10.1111:cgf.13547,
journal = {Computer Graphics Forum}, title = {{
Fast Global Illumination with Discrete Stochastic Microfacets Using a Filterable Model}},
author = {
Wang, Beibei
and
Wang, Lu
and
Holzschuch, Nicolas
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13547}
}
                
@article{
10.1111:cgf.13548,
journal = {Computer Graphics Forum}, title = {{
Feature Generation for Adaptive Gradient-Domain Path Tracing}},
author = {
Back, Jonghee
and
Yoon, Sung-Eui
and
Moon, Bochang
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13548}
}
                
@article{
10.1111:cgf.13549,
journal = {Computer Graphics Forum}, title = {{
Mumford-Shah Mesh Processing using the Ambrosio-Tortorelli Functional}},
author = {
Bonneel, Nicolas
and
Coeurjolly, David
and
Gueth, Pierre
and
Lachaud, Jacques-Olivier
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13549}
}
                
@article{
10.1111:cgf.13550,
journal = {Computer Graphics Forum}, title = {{
Ellipsoid Packing Structures on Freeform Surfaces}},
author = {
Xu, Qun-Ce
and
Deng, Bailin
and
Yang, Yong-Liang
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13550}
}
                
@article{
10.1111:cgf.13551,
journal = {Computer Graphics Forum}, title = {{
Controlling Stroke Size in Fast Style Transfer with Recurrent Convolutional Neural Network}},
author = {
Yang, Lingchen
and
Yang, Lumin
and
Zhao, Mingbo
and
Zheng, Youyi
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13551}
}
                
@article{
10.1111:cgf.13552,
journal = {Computer Graphics Forum}, title = {{
FashionGAN: Display your fashion design using Conditional Generative Adversarial Nets}},
author = {
Cui, Yi Rui
and
Liu, Qi
and
Gao, Cheng Ying
and
Su, Zhuo
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13552}
}
                
@article{
10.1111:cgf.13553,
journal = {Computer Graphics Forum}, title = {{
Reformulating Hyperelastic Materials with Peridynamic Modeling}},
author = {
Xu, Liyou
and
He, Xiaowei
and
Chen, Wei
and
Li, Sheng
and
Wang, Guoping
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13553}
}
                
@article{
10.1111:cgf.13554,
journal = {Computer Graphics Forum}, title = {{
Parallel Multigrid for Nonlinear Cloth Simulation}},
author = {
Wang, Zhendong
and
Wu, Longhua
and
Fratarcangeli, Marco
and
Tang, Min
and
Wang, Huamin
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13554}
}
                
@article{
10.1111:cgf.13555,
journal = {Computer Graphics Forum}, title = {{
Few-shot Learning of Homogeneous Human Locomotion Styles}},
author = {
Mason, Ian
and
Starke, Sebastian
and
Zhang, He
and
Bilen, Hakan
and
Komura, Taku
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13555}
}
                
@article{
10.1111:cgf.13556,
journal = {Computer Graphics Forum}, title = {{
Non-Local Low-Rank Normal Filtering for Mesh Denoising}},
author = {
Li, Xianzhi
and
Zhu, Lei
and
Fu, Chi-Wing
and
Heng, Pheng-Ann
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13556}
}
                
@article{
10.1111:cgf.13557,
journal = {Computer Graphics Forum}, title = {{
Reconstructing Flowers from Sketches}},
author = {
Bobenrieth, Cédric
and
Seo, Hyewon
and
Cordier, Frédéric
and
Habibi, Arash
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13557}
}
                
@article{
10.1111:cgf.13558,
journal = {Computer Graphics Forum}, title = {{
Dynamic Deep Octree for High-resolution Volumetric Painting in Virtual Reality}},
author = {
Kim, Yeojin
and
Kim, Byungmoon
and
Kim, Young J.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13558}
}
                
@article{
10.1111:cgf.13559,
journal = {Computer Graphics Forum}, title = {{
Uncut Aerial Video via a Single Sketch}},
author = {
Yang, Hao
and
Xie, Ke
and
Huang, Shengqiu
and
Huang, Hui
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13559}
}
                
@article{
10.1111:cgf.13560,
journal = {Computer Graphics Forum}, title = {{
Single Image Surface Appearance Modeling with Self-augmented CNNs and Inexact Supervision}},
author = {
Ye, Wenjie
and
Li, Xiao
and
Dong, Yue
and
Peers, Pieter
and
Tong, Xin
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13560}
}
                
@article{
10.1111:cgf.13561,
journal = {Computer Graphics Forum}, title = {{
Learning Scene Illumination by Pairwise Photos from Rear and Front Mobile Cameras}},
author = {
Cheng, Dachuan
and
Shi, Jian
and
Chen, Yanyun
and
Deng, Xiaoming
and
Zhang, Xiaopeng
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13561}
}
                
@article{
10.1111:cgf.13562,
journal = {Computer Graphics Forum}, title = {{
A Practical Approach to Physically-Based Reproduction of Diffusive Cosmetics}},
author = {
Kim, Goanghun
and
Ko, Hyeong-Seok
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13562}
}
                
@article{
10.1111:cgf.13563,
journal = {Computer Graphics Forum}, title = {{
Piecewise Linear Mapping Optimization Based on the Complex View}},
author = {
Golla, Björn
and
Seidel, Hans-Peter
and
Chen, Renjie
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13563}
}
                
@article{
10.1111:cgf.13564,
journal = {Computer Graphics Forum}, title = {{
A New Uniform Format for 360 VR Videos}},
author = {
Guo, Juan
and
Pei, Qikai K.
and
Ma, Guilong L.
and
Liu, Li
and
Zhang, Xinyu Y.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13564}
}
                
@article{
10.1111:cgf.13565,
journal = {Computer Graphics Forum}, title = {{
Instant Stippling on 3D Scenes}},
author = {
Ma, Lei
and
Guo, Jianwei
and
Yan, Dong-Ming
and
Sun, Hanqiu
and
Chen, Yanyun
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13565}
}
                
@article{
10.1111:cgf.13566,
journal = {Computer Graphics Forum}, title = {{
Deep Video Stabilization Using Adversarial Networks}},
author = {
Xu, Sen-Zhe
and
Hu, Jun
and
Wang, Miao
and
Mu, Tai-Jiang
and
Hu, Shi-Min
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13566}
}
                
@article{
10.1111:cgf.13567,
journal = {Computer Graphics Forum}, title = {{
Defocus and Motion Blur Detection with Deep Contextual Features}},
author = {
Kim, Beomseok
and
Son, Hyeongseok
and
Park, Seong-Jin
and
Cho, Sunghyun
and
Lee, Seungyong
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13567}
}
                
@article{
10.1111:cgf.13568,
journal = {Computer Graphics Forum}, title = {{
Generative Adversarial Image Super-Resolution Through Deep Dense Skip Connections}},
author = {
Zhu, Xiaobin
and
Li, Zhuangzi
and
Zhang, Xiaoyu
and
Li, Haisheng
and
Xue, Ziyu
and
Wang, Lei
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13568}
}
                
@article{
10.1111:cgf.13569,
journal = {Computer Graphics Forum}, title = {{
DMAT: Deformable Medial Axis Transform for Animated Mesh Approximation}},
author = {
Yang, Baorong
and
Yao, Junfeng
and
Guo, Xiaohu
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13569}
}
                
@article{
10.1111:cgf.13570,
journal = {Computer Graphics Forum}, title = {{
Improved Use of LOP for Curve Skeleton Extraction}},
author = {
Li, Lei
and
Wang, Wencheng
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13570}
}
                
@article{
10.1111:cgf.13571,
journal = {Computer Graphics Forum}, title = {{
Skeletex: Skeleton-texture Co-representation for Topology-driven Real-time Interchange and Manipulation of Surface Regions}},
author = {
Madaras, Martin
and
Riecický, Adam
and
Mesároš, Michal
and
Stuchlík, Martin
and
Piovarči, Michal
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13571}
}
                
@article{
10.1111:cgf.13572,
journal = {Computer Graphics Forum}, title = {{
Automatic Mechanism Modeling from a Single Image with CNNs}},
author = {
Lin, Minmin
and
Shao, Tianjia
and
Zheng, Youyi
and
Ren, Zhong
and
Weng, Yanlin
and
Yang, Yin
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13572}
}
                
@article{
10.1111:cgf.13573,
journal = {Computer Graphics Forum}, title = {{
Sit & Relax: Interactive Design of Body-Supporting Surfaces}},
author = {
Leimer, Kurt
and
Birsak, Michael
and
Rist, Florian
and
Musialski, Przemyslaw
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13573}
}
                
@article{
10.1111:cgf.13574,
journal = {Computer Graphics Forum}, title = {{
Shape and Pose Estimation for Closely Interacting Persons Using Multi-view Images}},
author = {
Li, Kun
and
Jiao, Nianhong
and
Liu, Yebin
and
Wang, Yangang
and
Yang, Jingyu
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13574}
}
                
@article{
10.1111:cgf.13575,
journal = {Computer Graphics Forum}, title = {{
Local and Hierarchical Refinement for Subdivision Gradient Meshes}},
author = {
Verstraaten, Teun W.
and
Kosinka, Jiri
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13575}
}
                
@article{
10.1111:cgf.13576,
journal = {Computer Graphics Forum}, title = {{
Modeling Fonts in Context: Font Prediction on Web Designs}},
author = {
Zhao, Nanxuan
and
Cao, Ying
and
Lau, Rynson W. H.
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13576}
}
                
@article{
10.1111:cgf.13577,
journal = {Computer Graphics Forum}, title = {{
Decomposing Images into Layers with Advanced Color Blending}},
author = {
Koyama, Yuki
and
Goto, Masataka
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13577}
}
                
@article{
10.1111:cgf.13578,
journal = {Computer Graphics Forum}, title = {{
Unsupervised Deep Single-Image Intrinsic Decomposition using Illumination-Varying Image Sequences}},
author = {
Lettry, Louis
and
Vanhoey, Kenneth
and
Van Gool, Luc
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13578}
}
                
@article{
10.1111:cgf.13579,
journal = {Computer Graphics Forum}, title = {{
Translucent Image Recoloring through Homography Estimation}},
author = {
Huang, Yifei
and
Wang, Changbo
and
Li, Chenhui
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13579}
}
                
@article{
10.1111:cgf.13580,
journal = {Computer Graphics Forum}, title = {{
Binocular Tone Mapping with Improved Overall Contrast and Local Details}},
author = {
Zhang, Zhuming
and
Hu, Xinghong
and
Liu, Xueting
and
Wong, Tien-Tsin
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13580}
}
                
@article{
10.1111:cgf.13581,
journal = {Computer Graphics Forum}, title = {{
GPU-based Polynomial Finite Element Matrix Assembly for Simplex Meshes}},
author = {
Mueller-Roemer, Johannes Sebastian
and
Stork, André
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13581}
}
                
@article{
10.1111:cgf.13582,
journal = {Computer Graphics Forum}, title = {{
Subdivision Schemes With Optimal Bounded Curvature Near Extraordinary Vertices}},
author = {
Ma, Yue
and
Ma, Weiyin
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13582}
}
                
@article{
10.1111:cgf.13583,
journal = {Computer Graphics Forum}, title = {{
Curvature Continuity Conditions Between Adjacent Toric Surface Patches}},
author = {
Sun, Lanyin
and
Zhu, Chungang
}, year = {
2018},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13583}
}

Browse

Recent Submissions

Now showing 1 - 43 of 43
  • Item
    Frontmatter: Pacific Graphics 2018
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Fu, Hongbo; Ghosh, Abhijeet; Kopf, Johannes; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
  • Item
    Online Global Non-rigid Registration for 3D Object Reconstruction Using Consumer-level Depth Cameras
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Xu, Jiamin; Xu, Weiwei; Yang, Yin; Deng, Zhigang; Bao, Hujun; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    We investigate how to obtain high-quality 360-degree 3D reconstructions of small objects using consumer-level depth cameras. For many homeware objects such as shoes and toys with dimensions around 0.06 - 0:4 meters, their whole projections, in the hand-held scanning process, occupy fewer than 20% pixels of the camera's image. We observe that existing 3D reconstruction algorithms like KinectFusion and other similar methods often fail in such cases even under the close-range depth setting. To achieve high-quality 3D object reconstruction results at this scale, our algorithm relies on an online global non-rigid registration, where embedded deformation graph is employed to handle the drifting of camera tracking and the possible nonlinear distortion in the captured depth data. We perform an automatic target object extraction from RGBD frames to remove the unrelated depth data so that the registration algorithm can focus on minimizing the geometric and photogrammetric distances of the RGBD data of target objects. Our algorithm is implemented using CUDA for a fast non-rigid registration. The experimental results show that the proposed method can reconstruct high-quality 3D shapes of various small objects with textures.
  • Item
    Biorthogonal Wavelet Surface Reconstruction Using Partial Integrations
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Ren, Xiaohua; Lyu, Luan; He, Xiaowei; Cao, Wei; Yang, Zhixin; Sheng, Bin; Zhang, Yanci; Wu, Enhua; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    We introduce a new biorthogonal wavelet approach to creating a water-tight surface defined by an implicit function, from a finite set of oriented points. Our approach aims at addressing problems with previous wavelet methods which are not resilient to missing or nonuniformly sampled data. To address the problems, our approach has two key elements. First, by applying a three-dimensional partial integration, we derive a new integral formula to compute the wavelet coefficients without requiring the implicit function to be an indicator function. It can be shown that the previously used formula is a special case of our formula when the integrated function is an indicator function. Second, a simple yet general method is proposed to construct smooth wavelets with small support. With our method, a family of wavelets can be constructed with the same support size as previously used wavelets while having one more degree of continuity. Experiments show that our approach can robustly produce results comparable to those produced by the Fourier and Poisson methods, regardless of the input data being noisy, missing or nonuniform. Moreover, our approach does not need to compute global integrals or solve large linear systems.
  • Item
    Semantic Reconstruction: Reconstruction of Semantically Segmented 3D Meshes via Volumetric Semantic Fusion
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Jeon, Junho; Jung, Jinwoong; Kim, Jungeon; Lee, Seungyong; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Semantic segmentation partitions a given image or 3D model of a scene into semantically meaning parts and assigns predetermined labels to the parts. With well-established datasets, deep networks have been successfully used for semantic segmentation of RGB and RGB-D images. On the other hand, due to the lack of annotated large-scale 3D datasets, semantic segmentation for 3D scenes has not yet been much addressed with deep learning. In this paper, we present a novel framework for generating semantically segmented triangular meshes of reconstructed 3D indoor scenes using volumetric semantic fusion in the reconstruction process. Our method integrates the results of CNN-based 2D semantic segmentation that is applied to the RGB-D stream used for dense surface reconstruction. To reduce the artifacts from noise and uncertainty of single-view semantic segmentation, we introduce adaptive integration for the volumetric semantic fusion and CRF-based semantic label regularization. With these methods, our framework can easily generate a high-quality triangular mesh of the reconstructed 3D scene with dense (i.e., per-vertex) semantic labels. Extensive experiments demonstrate that our semantic segmentation results of 3D scenes achieves the state-of-the-art performance compared to the previous voxel-based and point cloud-based methods.
  • Item
    Light Optimization for Detail Highlighting
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Gkaravelis, Anastasios; Papaioannou, Georgios; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    In this paper we propose an effective technique for the automatic arrangement of spot lights and other luminaires on or near user-provided arbitrary mounting surfaces in order to highlight the geometric details of complex objects. Since potential applications include the lighting design for exhibitions and similar installations, the method takes into account obstructing geometry and potential occlusion from visitors and other non-permanent blocking geometry. Our technique generates the most appropriate position and orientation for light sources based on a local contrast maximization near salient geometric features and a clustering mechanism, producing consistent and view-independent results, with minimal user intervention. We validate our method with realistic test cases including multiple and disjoint exhibits as well as high occlusion scenarios.
  • Item
    Directing the Photography: Combining Cinematic Rules, Indirect Light Controls and Lighting-by-Example
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Galvane, Quentin; Lino, Christophe; Christie, Marc; Cozot, Rémi; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    The placement of lights in a 3D scene is a technical and artistic task that requires time and trained skills. Most 3D modelling tools only provide a direct control of light sources, through the manipulation of parameters such as size, location, flux (the perceived power of light) or opening angle (the light frustum). Approaches have been relying on automated or semi-automated techniques to relieve users from such low-level manipulations at the expense of an important computational cost. In this paper, guided by discussions with experts in scene and object lighting, we propose an indirect control of area light sources. We first formalize the classical 3-point lighting design principle (key-light, fill-lights and back/rim-lights) in a parametric model. Given a key-light placed in the scene, we then provide a computational approach to (i) automatically compute the position and size of fill-lights and back/rim-lights by analyzing the geometry of 3D character, and (ii) automatically compute the flux and size of key, fill and back/rim lights, given a sample reference image in a computationally efficient way. Results demonstrate the benefits of the approach on the quick lighting of 3D characters, and further demonstrate the feasibility of interactive control of multiple lights through image features.
  • Item
    Fast Global Illumination with Discrete Stochastic Microfacets Using a Filterable Model
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Wang, Beibei; Wang, Lu; Holzschuch, Nicolas; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Many real-life materials have a sparkling appearance, whether by design or by nature. Examples include metallic paints, sparkling varnish but also snow. These sparkles correspond to small, isolated, shiny particles reflecting light in a specific direction, on the surface or embedded inside the material. The particles responsible for these sparkles are usually small and discontinuous. These characteristics make it diffcult to integrate them effciently in a standard rendering pipeline, especially for indirect illumination. Existing approaches use a 4-dimensional hierarchy, searching for light-reflecting particles simultaneously in space and direction. The approach is accurate, but still expensive. In this paper, we show that this 4-dimensional search can be approximated using separate 2-dimensional steps. This approximation allows fast integration of glint contributions for large footprints, reducing the extra cost associated with glints be an order of magnitude.
  • Item
    Feature Generation for Adaptive Gradient-Domain Path Tracing
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Back, Jonghee; Yoon, Sung-Eui; Moon, Bochang; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    In this paper, we propose a new technique to incorporate recent adaptive rendering approaches built upon local regression theory into a gradient-domain path tracing framework, in order to achieve high-quality rendering results. Our method aims to reduce random artifacts introduced by random sampling on image colors and gradients. Our high-level approach is to identify a feature image from noisy gradients, and pass the image to an existing local regression based adaptive method so that adaptive sampling and reconstruction using our feature can boost the performance of gradient-domain rendering. To fulfill our idea, we derive an ideal feature in the form of image gradients and propose an estimation process for the ideal feature in the presence of noise in image gradients. We demonstrate that our integrated adaptive solution leads to performance improvement for a gradient-domain path tracer, by seamlessly incorporating recent adaptive sampling and reconstruction strategies through our estimated feature.
  • Item
    Mumford-Shah Mesh Processing using the Ambrosio-Tortorelli Functional
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Bonneel, Nicolas; Coeurjolly, David; Gueth, Pierre; Lachaud, Jacques-Olivier; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    The Mumford-Shah functional approximates a function by a piecewise smooth function. Its versatility makes it ideal for tasks such as image segmentation or restoration, and it is now a widespread tool of image processing. Recent work has started to investigate its use for mesh segmentation and feature lines detection, but we take the stance that the power of this functional could reach far beyond these tasks and integrate the everyday mesh processing toolbox. In this paper, we discretize an Ambrosio-Tortorelli approximation via a Discrete Exterior Calculus formulation. We show that, combined with a new shape optimization routine, several mesh processing problems can be readily tackled within the same framework. In particular, we illustrate applications in mesh denoising, normal map embossing, mesh inpainting and mesh segmentation.
  • Item
    Ellipsoid Packing Structures on Freeform Surfaces
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Xu, Qun-Ce; Deng, Bailin; Yang, Yong-Liang; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Designers always get good inspirations from fascinating geometric structures gifted by the nature. In the recent years, various computational design tools have been proposed to help generate cell packing structures on freeform surfaces, which consist of a packing of simple primitives, such as polygons, spheres, etc. In this work, we aim at computationally generating novel ellipsoid packing structures on freeform surfaces. We formulate the problem as a generalization of sphere packing structures in the sense that anisotropic ellipsoids are used instead of isotropic spheres to pack a given surface. This is done by defining an anisotropic metric based on local surface anisotropy encoded by principal curvatures and the corresponding directions. We propose an optimization framework that can optimize the shapes of individual ellipsoids and the spatial relation between neighboring ellipsoids to form a quality packing structure. A tailored anisotropic remeshing method is also employed to better initialize the optimization and ensure the quality of the result. Our framework is extensively evaluated by optimizing ellipsoid packing and generating appealing geometric structures on a variety of freeform surfaces.
  • Item
    Controlling Stroke Size in Fast Style Transfer with Recurrent Convolutional Neural Network
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Yang, Lingchen; Yang, Lumin; Zhao, Mingbo; Zheng, Youyi; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Controlling stroke size in Fast Style Transfer remains a difficult task. So far, only a few attempts have been made towards it, and they still exhibit several deficiencies regarding efficiency, flexibility, and diversity. In this paper, we aim to tackle these problems and propose a recurrent convolutional neural subnetwork, which we call recurrent stroke-pyramid, to control the stroke size in Fast Style Transfer. Compared to the state-of-the-art methods, our method not only achieves competitive results with much fewer parameters but provides more flexibility and efficiency for generalizing to unseen larger stroke size and being able to produce a wide range of stroke sizes with only one residual unit. We further embed the recurrent stroke-pyramid into the Multi-Styles and the Arbitrary-Style models, achieving both style and stroke-size control in an entirely feed-forward manner with two novel run-time control strategies.
  • Item
    FashionGAN: Display your fashion design using Conditional Generative Adversarial Nets
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Cui, Yi Rui; Liu, Qi; Gao, Cheng Ying; Su, Zhuo; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Virtual garment display plays an important role in fashion design for it can directly show the design effect of the garment without having to make a sample garment like traditional clothing industry. In this paper, we propose an end-to-end virtual garment display method based on Conditional Generative Adversarial Networks. Different from existing 3D virtual garment methods which need complex interactions and domain-specific user knowledge, our method only need users to input a desired fashion sketch and a specified fabric image then the image of the virtual garment whose shape and texture are consistent with the input fashion sketch and fabric image can be shown out quickly and automatically. Moreover, it can also be extended to contour images and garment images, which further improves the reuse rate of fashion design. Compared with the existing image-to-image methods, the quality of images generated by our method is better in terms of color and shape.
  • Item
    Reformulating Hyperelastic Materials with Peridynamic Modeling
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Xu, Liyou; He, Xiaowei; Chen, Wei; Li, Sheng; Wang, Guoping; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Peridynamics is a formulation of the classical elastic theory that is targeted at simulating deformable objects with discontinuities, especially fractures. Till now, there are few studies that have been focused on how to model general hyperelastic materials with peridynamics. In this paper, we target at proposing a general strain energy function of hyperelastic materials for peridynamics. To get an intuitive model that can be easily controlled, we formulate the strain energy density function as a function parameterized by the dilatation and bond stretches, which can be decomposed into multiple one-dimensional functions independently. To account for nonlinear material behaviors, we also propose a set of nonlinear basis functions to help design a nonlinear strain energy function more easily. For an anisotropic material, we additionally introduce an anisotropic kernel to control the elastic behavior for each bond independently. Experiments show that our model is flexible enough to approximately regenerate various hyperelastic materials in classical elastic theory, including St.Venant-Kirchhoff and Neo-Hookean materials.
  • Item
    Parallel Multigrid for Nonlinear Cloth Simulation
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Wang, Zhendong; Wu, Longhua; Fratarcangeli, Marco; Tang, Min; Wang, Huamin; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Accurate high-resolution simulation of cloth is a highly desired computational tool in graphics applications. As singleresolution simulation starts to reach the limit of computational power, we believe the future of cloth simulation is in multi-resolution simulation. In this paper, we explore nonlinearity, adaptive smoothing, and parallelization under a full multigrid (FMG) framework. The foundation of this research is a novel nonlinear FMG method for unstructured meshes. To introduce nonlinearity into FMG, we propose to formulate the smoothing process at each resolution level as the computation of a search direction for the original high-resolution nonlinear optimization problem. We prove that our nonlinear FMG is guaranteed to converge under various conditions and we investigate the improvements to its performance. We present an adaptive smoother which is used to reduce the computational cost in the regions with low residuals already. Compared to normal iterative solvers, our nonlinear FMG method provides faster convergence and better performance for both Newton's method and Projective Dynamics. Our experiment shows our method is efficient, accurate, stable against large time steps, and friendly with GPU parallelization. The performance of the method has a good scalability to the mesh resolution, and the method has good potential to be combined with multi-resolution collision handling for real-time simulation in the future.
  • Item
    Few-shot Learning of Homogeneous Human Locomotion Styles
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Mason, Ian; Starke, Sebastian; Zhang, He; Bilen, Hakan; Komura, Taku; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Using neural networks for learning motion controllers from motion capture data is becoming popular due to the natural and smooth motions they can produce, the wide range of movements they can learn and their compactness once they are trained. Despite these advantages, these systems require large amounts of motion capture data for each new character or style of motion to be generated, and systems have to undergo lengthy retraining, and often reengineering, to get acceptable results. This can make the use of these systems impractical for animators and designers and solving this issue is an open and rather unexplored problem in computer graphics. In this paper we propose a transfer learning approach for adapting a learned neural network to characters that move in different styles from those on which the original neural network is trained. Given a pretrained character controller in the form of a Phase-Functioned Neural Network for locomotion, our system can quickly adapt the locomotion to novel styles using only a short motion clip as an example. We introduce a canonical polyadic tensor decomposition to reduce the amount of parameters required for learning from each new style, which both reduces the memory burden at runtime and facilitates learning from smaller quantities of data. We show that our system is suitable for learning stylized motions with few clips of motion data and synthesizing smooth motions in real-time.
  • Item
    Non-Local Low-Rank Normal Filtering for Mesh Denoising
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Li, Xianzhi; Zhu, Lei; Fu, Chi-Wing; Heng, Pheng-Ann; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    This paper presents a non-local low-rank normal filtering method for mesh denoising. By exploring the geometric similarity between local surface patches on 3D meshes in the form of normal fields, we devise a low-rank recovery model that filters normal vectors by means of patch groups. In summary, our method has the following key contributions. First, we present the guided normal patch covariance descriptor to analyze the similarity between patches. Second, we pack normal vectors on similar patches into the normal-field patch-group (NPG) matrix for rank analysis. Third, we formulate mesh denoising as a low-rank matrix recovery problem based on the prior that the rank of the NPG matrix is high for raw meshes with noise, but can be significantly reduced for denoised meshes, whose normal vectors across similar patches should be more strongly correlated. Furthermore, we devise an objective function based on an improved truncated 'gamma' norm, and derive an optimization procedure using the alternative direction method of multipliers and iteratively re-weighted least squares techniques.We conducted several experiments to evaluate our method using various 3D models, and compared our results against several state-of-the-art methods. Experimental results show that our method consistently outperforms other methods and better preserves the fine details.
  • Item
    Reconstructing Flowers from Sketches
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Bobenrieth, Cédric; Seo, Hyewon; Cordier, Frédéric; Habibi, Arash; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    As the symbol of beauty, floral objects have been one of the most popular subjects of artistic drawing. However, designing 3D floral models is generally time- and resource-consuming, because of their structural and geometrical complexity. In this paper, we address the problem of reconstructing floral objects from sketch input. The user draws a relatively clean sketch of a flower and a few additional guide markings from an arbitrary view to rapidly create quality geometric models of flowers. Our system offers a novel modeling scheme compared to several existing flower modelers accepting sketch as input, where the user is required to work with different views, providing step-by-step sketch input. Given the silhouette and the guide strokes, an assumed, common botanical structure is estimated, i.e. a cone for each ring of petals. The cones and the silhouette sketch that we segment into elementary curves are used to retrieve model elements from the pre-constructed shape database. These elements are then placed together around the cone, where an additional, per-element deformation is performed so as to maximize the silhouette similarity between the user sketch and the 3D flower model from the chosen view. Our system has shown to robustly create a variety of flowers in various configurations, including flower models with several petal layers and various blooming degrees, drawn from different views.
  • Item
    Dynamic Deep Octree for High-resolution Volumetric Painting in Virtual Reality
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kim, Yeojin; Kim, Byungmoon; Kim, Young J.; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    With virtual reality, digital painting on 2D canvas is now being extended to 3D space. In this paper, we generalize the 2D pixel canvas to a 3D voxel canvas to allow artists to synthesize volumetric color fields. We develop a deep and dynamic octree-based painting and rendering system using both CPU and GPU to take advantage of the characteristics of both processors (CPU for octree modeling and GPU for volume rendering). On the CPU-side, we dynamically adjust an octree and incrementally update the octree to GPU with low latency without compromising the frame rates of the rendering. Our octree is balanced and uses a novel 3-neighbor connectivity for format simplicity and efficient storage, while allowing constant neighbor access time in ray casting. To further reduce the GPU-side 3-neighbor computations, we precompute a culling mask in CPU and upload it to GPU. Finally, we analyze the numerical error-propagation in ray casting through high resolution octree and present a theoretical error bound.
  • Item
    Uncut Aerial Video via a Single Sketch
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Yang, Hao; Xie, Ke; Huang, Shengqiu; Huang, Hui; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Nowadays UAV filming is getting popular, more and more stunning aerial videos appearing online. Nonetheless, making a good uncut aerial video with only one-long-shot for the large-scale outdoor scenes is still quite challenging, no many eye-catching pieces available yet. It requires users to have both consummate drone controlling skill and good perception of filming aesthetics. If totally manual, the user has to simultaneously adjust the drone position and the mounted camera orientation during the whole flyby while trying to keep all operation changes executed smoothly. Recent research has proposed a number of planning tools for automatic or semi-automatic aerial videography, however, most requires rather complex user inputs and heavy computations. In this paper, we propose a user-friendly system designed to simplify the input and automatically generate continuous camera moves to capture compelling aerial videos that users prefer to see without any post cutting or editing. Assume a rough 2.5D scene model that includes all the regions of interest are available, users are only required to casually draw a single sketch on the 2D map. Our system will analyze this rough sketch input, compute the corresponding quality views in 3D safe flying zone, and then create a globally optimal camera trajectory passing through regions of user interest via solving a combinatorial problem. At end, we optimize the drone flying speed locally to make the resulting aerial videos more visually pleasing.
  • Item
    Single Image Surface Appearance Modeling with Self-augmented CNNs and Inexact Supervision
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Ye, Wenjie; Li, Xiao; Dong, Yue; Peers, Pieter; Tong, Xin; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    This paper presents a deep learning based method for estimating the spatially varying surface reflectance properties from a single image of a planar surface under unknown natural lighting trained using only photographs of exemplar materials without referencing any artist generated or densely measured spatially varying surface reflectance training data. Our method is based on an empirical study of Li et al.'s [LDPT17] self-augmentation training strategy that shows that the main role of the initial approximative network is to provide guidance on the inherent ambiguities in single image appearance estimation. Furthermore, our study indicates that this initial network can be inexact (i.e., trained from other data sources) as long as it resolves the inherent ambiguities. We show that the single image estimation network trained without manually labeled data outperforms prior work in terms of accuracy as well as generality.
  • Item
    Learning Scene Illumination by Pairwise Photos from Rear and Front Mobile Cameras
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Cheng, Dachuan; Shi, Jian; Chen, Yanyun; Deng, Xiaoming; Zhang, Xiaopeng; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Illumination estimation is an essential problem in computer vision, graphics and augmented reality. In this paper, we propose a learning based method to recover low-frequency scene illumination represented as spherical harmonic (SH) functions by pairwise photos from rear and front cameras on mobile devices. An end-to-end deep convolutional neural network (CNN) structure is designed to process images on symmetric views and predict SH coefficients. We introduce a novel Render Loss to improve the rendering quality of the predicted illumination. A high quality high dynamic range (HDR) panoramic image dataset was developed for training and evaluation. Experiments show that our model produces visually and quantitatively superior results compared to the state-of-the-arts. Moreover, our method is practical for mobile-based applications.
  • Item
    A Practical Approach to Physically-Based Reproduction of Diffusive Cosmetics
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kim, Goanghun; Ko, Hyeong-Seok; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    In this paper, we introduce so-called the bSX method as a new way to utilize the Kubelka-Munk (K-M) model. Assuming the material is completely diffusive, the K-M model gives the reflectance and transmittance of the material from the observation of the material applied on a backing, where the observation includes the thickness of the material application. By rearranging the original K-M equation, we propose that the reflectance and transmittance can be calculated without knowing the thickness. This is a practically useful contribution. Based on the above finding, we develop the bSX method which can (1) capture the material specific parameters from the two photos - taken before and after the material application, and (2) reproduce its effect on a novel backing. We experimented the proposed method in various cases related to virtual cosmetic try-on, which include (1) capture from a single color backing, (2) capture from human skin backing, (3) reproduction of varying thickness effect, (4) reproduction of multi-layer cosmetic application effect, (5) applying the proposed method to makeup transfer. Compared to previous image-based makeup transfer methods, the bSX method reproduces the feel of the cosmetics more accurately.
  • Item
    Piecewise Linear Mapping Optimization Based on the Complex View
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Golla, Björn; Seidel, Hans-Peter; Chen, Renjie; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    We present an efficient modified Newton iteration for the optimization of nonlinear energies on triangle meshes. Noting that the linear mapping between any pair of triangles is a special case of harmonic mapping, we build upon the results of Chen and Weber [CW17]. Based on the complex view of the linear mapping, we show that the Hessian of the isometric energies has a simple and compact analytic expression. This allows us to analytically project the per-element Hessians to positive semidefinite matrices for efficient Newton iteration. We show that our method outperforms state-of-the-art methods on 2D deformation and parameterization. Further, we inspect the spectra of the per triangle energy Hessians and show that given an initial mapping, simple global scaling can shift the energy towards a more convex state. This allows Newton iteration to converge faster than starting from the given initial state. Additionally, our formulations support adding an energy smoothness term to the optimization with little additional effort, which improves the mapping results such that concentrated distortions are reduced.
  • Item
    A New Uniform Format for 360 VR Videos
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Guo, Juan; Pei, Qikai K.; Ma, Guilong L.; Liu, Li; Zhang, Xinyu Y.; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Recent breakthroughs in VR technologies, especially in economic VR headsets and massive smartphones are creating a fastgrowing demand for 3D immersive VR content. 360 VR videos record a surrounding environment in every direction and give users a fully immersive experience. Thanks to a ton of 360 cameras that launched in the past years, 360 video content creation is exploding and 360 VR videos are becoming a new video standard in the digital industry. When ERP and CMP are perhaps the most prevalent projection and packing layout for storing 360 VR videos, they have severe projection distortion, internal discontinuous seams or disadvantages in aspect ratio. We introduce a new format for packing and storing 360 VR videos using two stage mappings. Hemispheres are seamlessly and uniformly mapped onto squares. Two respective squares are stitched to form a rectangle with the aspect ratio 2 : 1. Our approach is able to avoid internal discontinuity and generate uniform pixel distribution, while keeping the aspect ratio close to the majority standard aspect ratio of 16 : 9.
  • Item
    Instant Stippling on 3D Scenes
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Ma, Lei; Guo, Jianwei; Yan, Dong-Ming; Sun, Hanqiu; Chen, Yanyun; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    In this paper, we present a novel real-time approach to generate high-quality stippling on 3D scenes. The proposed method is built on a precomputed 2D sample sequence called incremental Voronoi set with blue-noise properties. A rejection sampling scheme is then applied to achieve tone reproduction, by thresholding the sample indices proportional to the inverse target tonal value to produce a suitable stipple density. Our approach is suitable for stippling large-scale or even dynamic scenes because the thresholding of individual stipples is trivially parallelizable. In addition, the static nature of the underlying sequence benefits the frame-to-frame coherence of the stippling. Finally, we propose an extension that supports stipples of varying sizes and tonal values, leading to smoother spatial and temporal transitions. Experimental results reveal that the temporal coherence and real-time performance of our approach are superior to those of previous approaches.
  • Item
    Deep Video Stabilization Using Adversarial Networks
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Xu, Sen-Zhe; Hu, Jun; Wang, Miao; Mu, Tai-Jiang; Hu, Shi-Min; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Video stabilization is necessary for many hand-held shot videos. In the past decades, although various video stabilization methods were proposed based on the smoothing of 2D, 2.5D or 3D camera paths, hardly have there been any deep learning methods to solve this problem. Instead of explicitly estimating and smoothing the camera path, we present a novel online deep learning framework to learn the stabilization transformation for each unsteady frame, given historical steady frames. Our network is composed of a generative network with spatial transformer networks embedded in different layers, and generates a stable frame for the incoming unstable frame by computing an appropriate affine transformation. We also introduce an adversarial network to determine the stability of a piece of video. The network is trained directly using the pair of steady and unsteady videos. Experiments show that our method can produce similar results as traditional methods, moreover, it is capable of handling challenging unsteady video of low quality, where traditional methods fail, such as video with heavy noise or multiple exposures. Our method runs in real time, which is much faster than traditional methods.
  • Item
    Defocus and Motion Blur Detection with Deep Contextual Features
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kim, Beomseok; Son, Hyeongseok; Park, Seong-Jin; Cho, Sunghyun; Lee, Seungyong; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    We propose a novel approach for detecting two kinds of partial blur, defocus and motion blur, by training a deep convolutional neural network. Existing blur detection methods concentrate on designing low-level features, but those features have difficulty in detecting blur in homogeneous regions without enough textures or edges. To handle such regions, we propose a deep encoder-decoder network with long residual skip-connections and multi-scale reconstruction loss functions to exploit high-level contextual features as well as low-level structural features. Another difficulty in partial blur detection is that there are no available datasets with images having both defocus and motion blur together, as most existing approaches concentrate only on either defocus or motion blur. To resolve this issue, we construct a synthetic dataset that consists of complex scenes with both types of blur. Experimental results show that our approach effectively detects and classifies blur, outperforming other state-of-the-art methods. Our method can be used for various applications, such as photo editing, blur magnification, and deblurring.
  • Item
    Generative Adversarial Image Super-Resolution Through Deep Dense Skip Connections
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Zhu, Xiaobin; Li, Zhuangzi; Zhang, Xiaoyu; Li, Haisheng; Xue, Ziyu; Wang, Lei; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Recently, image super-resolution works based on Convolutional Neural Networks (CNNs) and Generative Adversarial Nets (GANs) have shown promising performance. However, these methods tend to generate blurry and over-smoothed super-resolved (SR) images, due to the incomplete loss function and powerless architectures of networks. In this paper, a novel generative adversarial image super-resolution through deep dense skip connections (GSR-DDNet), is proposed to solve the above-mentioned problems. It aims to take advantage of GAN's ability of modeling data distributions, so that GSR-DDNet can select informative feature representation and model the mapping across the low-quality and high-quality images in an adversarial way. The pipeline of the proposed method consists of three main components: 1) The generator of a novel dense skip connection network with the deep structure for learning robust mapping function is proposed to generate SR images from low-resolution images; 2) The feature extraction network based on VGG-19 is adopted to capture high frequency feature maps for content loss; and 3) The discriminator with Wasserstein distance is adopted to identify the overall style of SR and ground-truth images. Experiments conducted on four publicly available datasets demonstrate the superiority against the state-of-the-art methods.
  • Item
    DMAT: Deformable Medial Axis Transform for Animated Mesh Approximation
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Yang, Baorong; Yao, Junfeng; Guo, Xiaohu; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Extracting a faithful and compact representation of an animated surface mesh is an important problem for computer graphics. However, the surface-based methods have limited approximation power for volume preservation when the animated sequences are extremely simplified. In this paper, we introduce Deformable Medial Axis Transform (DMAT), which is deformable medial mesh composed of a set of animated spheres. Starting from extracting an accurate and compact representation of a static MAT as the template and partitioning the vertices on the input surface as the correspondences for each medial primitive, we present a correspondence-based approximation method equipped with an As-Rigid-As-Possible (ARAP) deformation energy defined on medial primitives. As a result, our algorithm produces DMAT with consistent connectivity across the whole sequence, accurately approximating the input animated surfaces.
  • Item
    Improved Use of LOP for Curve Skeleton Extraction
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Li, Lei; Wang, Wencheng; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    It remains a challenge to robustly and rapidly extract high quality curve skeletons from 3D models of closed surfaces, especially when there are nearby surface sheets. In this paper, we address this challenge by improving the use of LOP (Locally Optimal Projection) to adaptively contract medial surfaces of 3D models. LOP was originally designed to optimize a raw scanned point cloud to its corresponding geometry surface. It has the effect of contraction, and the contraction amplitude is controlled by a support radius. Our improvements are twofold. First, we constrain the LOP operator applied in the 2D medial surface instead of in the 3D space and take a local region growing strategy to find neighborhoods for implementing LOP. Thus, we avoid interference between disconnected surface parts and accelerate the process due to the reduced search space. Second, we adaptively adjust the support radii to have different parts of the medial surface contracted adaptively and synchronously for generating connected skeletal curves. In this paper, we demonstrate that our method allows for each part of the medial surface to be contracted symmetrically to its center line and is insensitive to surface noises. Thus, with our method, centered and connected high quality curve skeletons can be extracted robustly and rapidly, even for models with nearby surface sheets. Experimental results highlight the effectiveness and high efficiency of the method, even for noisy and topologically complex models, making it superior to other state-of-the-art methods.
  • Item
    Skeletex: Skeleton-texture Co-representation for Topology-driven Real-time Interchange and Manipulation of Surface Regions
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Madaras, Martin; Riecický, Adam; Mesároš, Michal; Stuchlík, Martin; Piovarči, Michal; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Mesh processing algorithms depend on quick access to the local neighborhood, which requires costly memory queries. Moreover, even having access to the local neighborhood is not enough to efficiently perform many geometry processing algorithms in an automatic or semi-automatic way. As humans, we often imagine mesh editing at the level of topological information, e.g., altering surface features, adding limbs, etc., which is not supported by current data structures. These limitations come from the widely used mesh representations because the needed information is not implicitly defined by the structure. We propose a novel model representation called Skeletex. Each 3D model is decomposed into two elements: a skeletal structure that encodes the model topology and a vector displacement map to capture fine details of the geometry. Such a co-representation contains the topology information, as well as the information about the local vertex neighborhood at each texel. Additionally, our data structure facilitates an automatic skeleton-based cross-parameterization. This allows us to implement the mesh manipulation tasks in parallel, using a unified streamlined pipeline that directly maps to the GPU. We demonstrate the capabilities of our data structure by implementing surface region transfer and mesh morphing of 3D models.
  • Item
    Automatic Mechanism Modeling from a Single Image with CNNs
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Lin, Minmin; Shao, Tianjia; Zheng, Youyi; Ren, Zhong; Weng, Yanlin; Yang, Yin; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    This paper presents a novel system that enables a fully automatic modeling of both 3D geometry and functionality of a mechanism assembly from a single RGB image. The resulting 3D mechanism model highly resembles the one in the input image with the geometry, mechanical attributes, connectivity, and functionality of all the mechanical parts prescribed in a physically valid way. This challenging task is realized by combining various deep convolutional neural networks to provide high-quality and automatic part detection, segmentation, camera pose estimation and mechanical attributes retrieval for each individual part component. On the top of this, we use a local/global optimization algorithm to establish geometric interdependencies among all the parts while retaining their desired spatial arrangement. We use an interaction graph to abstract the inter-part connection in the resulting mechanism system. If an isolated component is identified in the graph, our system enumerates all the possible solutions to restore the graph connectivity, and outputs the one with the smallest residual error. We have extensively tested our system with a wide range of classic mechanism photos, and experimental results show that the proposed system is able to build high-quality 3D mechanism models without user guidance.
  • Item
    Sit & Relax: Interactive Design of Body-Supporting Surfaces
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Leimer, Kurt; Birsak, Michael; Rist, Florian; Musialski, Przemyslaw; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    We propose a novel method for interactive design of well-fitting body-supporting surfaces that is driven by the pressure distribution on the body's surface. Our main contribution is an interactive modeling system that utilizes captured body poses and computes an importance field that is proportional to the pressure distribution on the body for a given pose. This distribution indicates where the body should be supported in order to easily hold a particular pose, which is one of the measures of comfortable sitting. Using our approximation, we propose the entire workflow for interactive design of C2 smooth surfaces which serve as seats, or generally, as body supporting furniture for comfortable sitting. Finally, we also provide a design tool for RHINOCEROS/GRASSHOPPER that allows for interactive creation of single designs or entire multi-person sitting scenarios. We also test the tool with design students and present several results. Our method aims at interactive design in order to help designers to create appropriate surfaces digitally without additional empirical design passes.
  • Item
    Shape and Pose Estimation for Closely Interacting Persons Using Multi-view Images
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Li, Kun; Jiao, Nianhong; Liu, Yebin; Wang, Yangang; Yang, Jingyu; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Multi-person pose and shape estimation is very challenging, especially when the persons have close interactions. Existing methods only work well when people are well spaced out in the captured images. However, close interaction among people is very common in real life, which is more challenge due to complex articulation, frequent occlusion and inherent ambiguities. We present a fully-automatic markerless motion capture method to simultaneously estimate 3D poses and shapes of closely interacting people from multi-view sequences. We first predict the 2D joints for each person in an image, and then design a spatio-temporal tracker for multi-person pose tracking based on multi-view videos. Finally, we estimate 3D poses and shapes of all the persons with multi-view constraints using a skinned multi-person linear model (SMPL). Experimental results demonstrate that our method achieves fast but accurate pose and shape estimation results for multi-person close interaction cases. Compared with existing methods, our method does not need pre-segmentation for each person and manual intervention, which greatly reduces the complexity of the system including time complexity and system processing complexity.
  • Item
    Local and Hierarchical Refinement for Subdivision Gradient Meshes
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Verstraaten, Teun W.; Kosinka, Jiri; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Gradient mesh design tools allow users to create detailed scalable images, traditionally through the creation and manipulation of a (dense) mesh with regular rectangular topology. Through recent advances it is now possible to allow gradient meshes to have arbitrary manifold topology, using a modified Catmull-Clark subdivision scheme to define the resultant geometry and colour [LKSD17]. We present two novel methods to allow local and hierarchical refinement of both colour and geometry for such subdivision gradient meshes. Our methods leverage the mesh properties that the particular subdivision scheme ensures. In both methods, the artists enjoy all the standard capabilities of manipulating the mesh and the associated colour gradients at the coarsest level as well as locally at refined levels. Further novel features include interpolation of both position and colour of the vertices of the input meshes, local detail follows coarser-level edits, and support for sharp colour transitions, all at any level in the hierarchy offered by subdivision.
  • Item
    Modeling Fonts in Context: Font Prediction on Web Designs
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Zhao, Nanxuan; Cao, Ying; Lau, Rynson W. H.; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Web designers often carefully select fonts to fit the context of a web design to make the design look aesthetically pleasing and effective in communication. However, selecting proper fonts for a web design is a tedious and time-consuming task, as each font has many properties, such as font face, color, and size, resulting in a very large search space. In this paper, we aim to model fonts in context, by studying a novel and challenging problem of predicting fonts that match a given web design. To this end, we propose a novel, multi-task deep neural network to jointly predict font face, color and size for each text element on a web design, by considering multi-scale visual features and semantic tags of the web design. To train our model, we have collected a CTXFont dataset, which consists of 1k professional web designs, with labeled font properties. Experiments show that our model outperforms the baseline methods, achieving promising qualitative and quantitative results on the font selection task. We also demonstrate the usefulness of our method in a font selection task via a user study.
  • Item
    Decomposing Images into Layers with Advanced Color Blending
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Koyama, Yuki; Goto, Masataka; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Digital paintings are often created by compositing semi-transparent layers using various advanced color-blend modes, such as ''color-burn,'' ''multiply,'' and ''screen,'' which can produce interesting non-linear color effects. We propose a method of decomposing an input image into layers with such advanced color blending. Unlike previous layer-decomposition methods, which typically support only linear color-blend modes, ours can handle any user-specified color-blend modes. To enable this, we generalize a previous color-unblending formulation, in which only a specific layering model was considered. We also introduce several techniques for adapting our generalized formulation to practical use, such as the post-processing for refining smoothness. Our method lets users explore possible decompositions to find the one that matches for their purposes by manipulating the target color-blend mode and desired color distribution for each layer, as well as the number of layers. Thus, the output of our method is a layered, easily editable image composition organized in a way that digital artists are familiar with. Our method is useful for remixing existing illustrations, flexibly editing single-layer paintings, and bringing physically painted media (e.g., oil paintings) into a digital workflow.
  • Item
    Unsupervised Deep Single-Image Intrinsic Decomposition using Illumination-Varying Image Sequences
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Lettry, Louis; Vanhoey, Kenneth; Van Gool, Luc; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Machine learning based Single Image Intrinsic Decomposition (SIID) methods decompose a captured scene into its albedo and shading images by using the knowledge of a large set of known and realistic ground truth decompositions. Collecting and annotating such a dataset is an approach that cannot scale to sufficient variety and realism. We free ourselves from this limitation by training on unannotated images. Our method leverages the observation that two images of the same scene but with different lighting provide useful information on their intrinsic properties: by definition, albedo is invariant to lighting conditions, and cross-combining the estimated albedo of a first image with the estimated shading of a second one should lead back to the second one's input image. We transcribe this relationship into a siamese training scheme for a deep convolutional neural network that decomposes a single image into albedo and shading. The siamese setting allows us to introduce a new loss function including such cross-combinations, and to train solely on (time-lapse) images, discarding the need for any ground truth annotations. As a result, our method has the good properties of i) taking advantage of the time-varying information of image sequences in the (pre-computed) training step, ii) not requiring ground truth data to train on, and iii) being able to decompose single images of unseen scenes at runtime. To demonstrate and evaluate our work, we additionally propose a new rendered dataset containing illumination-varying scenes and a set of quantitative metrics to evaluate SIID algorithms. Despite its unsupervised nature, our results compete with state of the art methods, including supervised and non data-driven methods.
  • Item
    Translucent Image Recoloring through Homography Estimation
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Huang, Yifei; Wang, Changbo; Li, Chenhui; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Image color editing techniques are of great significance for users who wish to adjust the image color. However, previous works paid less attention to the translucent images. In this paper, we propose a new method to recolor the translucent images while preserving detailed information and color relationships of the source image. We consider the recolor problem as a location transformation problem and solve it in two steps: automatic palette extraction and homography estimation. First, we propose the Hmeans method to extract the dominant colors of the source image based on histogram statistics and clustering. Then, we propose homography estimation to map the source colors to desired colors in the CIE-LAB color space. Further, we adopt a non-linear optimization approach to improve the result generated by the last step. The proposed method maintains high fidelity of the source image. Experiments have shown that our method generates a state-of-the-art visual result, in particular in the shadow areas. The source images with ground truth generated by a ray tracer further verify the effectiveness of our method.
  • Item
    Binocular Tone Mapping with Improved Overall Contrast and Local Details
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Zhang, Zhuming; Hu, Xinghong; Liu, Xueting; Wong, Tien-Tsin; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Tone mapping is a commonly used technique that maps the set of colors in high-dynamic-range (HDR) images to another set of colors in low-dynamic-range (LDR) images, to fit the need for print-outs, LCD monitors and projectors. Unfortunately, during the compression of dynamic range, the overall contrast and local details generally cannot be preserved simultaneously. Recently, with the increased use of stereoscopic devices, the notion of binocular tone mapping has been proposed in the existing research study. However, the existing research lacks the binocular perception study and is unable to generate the optimal binocular pair that presents the most visual content. In this paper, we propose a novel perception-based binocular tone mapping method, that can generate an optimal binocular image pair (generating left and right images simultaneously) from an HDR image that presents the most visual content by designing a binocular perception metric. Our method outperforms the existing method in terms of both visual and time performance.
  • Item
    GPU-based Polynomial Finite Element Matrix Assembly for Simplex Meshes
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Mueller-Roemer, Johannes Sebastian; Stork, André; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    In this paper, we present a matrix assembly technique for arbitrary polynomial order finite element simulations on simplex meshes for graphics processing units (GPU). Compared to the current state of the art in GPU-based matrix assembly, we avoid the need for an intermediate sparse matrix and perform assembly directly into the final, GPU-optimized data structure. Thereby, we avoid the resulting 180% to 600% memory overhead, depending on polynomial order, and associated allocation time, while simplifying the assembly code and using a more compact mesh representation. We compare our method with existing algorithms and demonstrate significant speedups.
  • Item
    Subdivision Schemes With Optimal Bounded Curvature Near Extraordinary Vertices
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Ma, Yue; Ma, Weiyin; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    We present a novel method to construct subdivision stencils near extraordinary vertices with limit surfaces having optimal bounded curvature at extraordinary positions. With the proposed method, subdivision stencils for newly inserted and updated vertices near extraordinary vertices are first constructed to ensure subdivision with G1 continuity and bounded curvature at extraordinary positions. The remaining degrees of freedom of the constructed subdivision stencils are further used to optimize the eigenbasis functions corresponding to the subsubdominant eigenvalues of the subdivision with respect to G2 continuity constraints. We demonstrate the method by replacing subdivision stencils near extraordinary vertices for Catmull-Clark subdivision and compare the results with the original Catmull-Clark subdivision and previous tuning schemes known with small curvature variation near extraordinary positions. The results show that the proposed method produces subdivision schemes with better or comparable curvature behavior around extraordinary vertices with comparatively simple subdivision stencils.
  • Item
    Curvature Continuity Conditions Between Adjacent Toric Surface Patches
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Sun, Lanyin; Zhu, Chungang; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Toric surface patch is the multi-sided generalization of classical Bézier surface patch. Geometric continuity of the parametric surface patches plays a crucial role in geometric modeling. In this paper, the necessary and sufficient conditions of curvature continuity between toric surface patches are illustrated with the theory of toric degeneration. Furthermore, some practical sufficient conditions of curvature continuity of toric surface patches are also developed.