DSpace Repository

Search Results

Now showing 1 - 10 of 224

Extracting Microfacet-based BRDF Parameters from Arbitrary Materials with Power Iterations
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Dupuy, Jonathan; Heitz, Eric; Iehl, Jean-Claude; Poulin, Pierre; Ostromoukhov, Victor; Jaakko Lehtinen and Derek Nowrouzezahrai
We introduce a novel fitting procedure that takes as input an arbitrary material, possibly anisotropic, and automatically converts it to a microfacet BRDF. Our algorithm is based on the property that the distribution of microfacets may be retrieved by solving an eigenvector problem that is built solely from backscattering samples. We show that the eigenvector associated to the largest eigenvalue is always the only solution to this problem, and compute it using the power iteration method. This approach is straightforward to implement, much faster to compute, and considerably more robust than solutions based on nonlinear optimizations. In addition, we provide simple conversion procedures of our fits into both Beckmann and GGX roughness parameters, and discuss the advantages of microfacet slope space to make our fits editable. We apply our method to measured materials from two large databases that include anisotropic materials, and demonstrate the benefits of spatially varying roughness on texture mapped geometric models.
CoWRadar: Visual Quantification of the Circle of Willis in Stroke Patients
(The Eurographics Association, 2015) Miao, Haichao; Mistelbauer, Gabriel; Našel, Christian; Gröller, M. Eduard; Katja Bühler and Lars Linsen and Nigel W. John
This paper presents a method for the visual quantification of cerebral arteries, known as the Circle of Willis (CoW). The CoW is an arterial structure that is responsible for the brain's blood supply. Dysfunctions of this arterial circle can lead to strokes. The diagnosis relies on the radiologist's expertise and the software tools used. These tools consist of very basic display methods of the volumetric data without support of advanced technologies in medical image processing and visualization. The goal of this paper is to create an automated method for the standardized description of cerebral arteries in stroke patients in order to provide an overview of the CoW's configuration. This novel display provides visual indications of problematic areas as well as straightforward comparisons between multiple patients. Additionally, we offer a pipeline for extracting the CoW from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) data sets. An enumeration technique for the labeling of the arterial segments is therefore suggested. We also propose a method for detecting the CoW's main supplying arteries by analyzing the coronal, sagittal and transverse image planes of the data sets. We evaluated the feasibility of our visual quantification approach in a study of 63 TOF-MRA data sets and compared our findings to those of three radiologists. The obtained results demonstrate that our proposed techniques are effective in detecting the arteries of the CoW.
Parallelized Global Brain Tractography
(The Eurographics Association, 2013) Philips, Stefan; Hlawitschka, Mario; Scheuermann, Gerik; Michael Bronstein and Jean Favre and Kai Hormann
Most brain tractography algorithms suffer from lower accuracy, because they use only information in a certain neighborhood and reconstruct the tracts independently. Global brain tractography algorithms compensate the lack of accuracy of those local algorithms in certain areas by optimizing the whole tractogram. The global tractography approach by Reisert et al. showed the best results in the Fiber Cup contest, but the runtime is still a matter for a medical application. In this paper we present the non-trivial parallelization of this global tractography algorithm. The parallelization exploits properties of the algorithm and modifies the algorithm where necessary. We compare the runtimes of the serial and the parallel variant and show that the outcomes of the parallel variant are of the same quality as those of the serial algorithm. The experiments proof also that the parallelization scales well for real world datasets.
Recent Advances in Adaptive Sampling and Reconstruction for Monte Carlo Rendering
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Zwicker, Matthias; Jarosz, Wojciech; Lehtinen, Jaakko; Moon, Bochang; Ramamoorthi, Ravi; Rousselle, Fabrice; Sen, Pradeep; Soler, Cyril; Yoon, Sungeui E.; K. Hormann and O. Staadt
Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggregating samples in a reconstruction step, possibly over large image regions. In this paper we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process. They typically estimate the errors of several reconstruction filters, and select the best filter locally to minimize error. We discuss advantages and disadvantages of recent state-of-the-art techniques, and provide visual and quantitative comparisons. Some of these techniques are proving useful in real-world applications, and we aim to provide an overview for practitioners and researchers to assess these approaches. In addition, we discuss directions for potential further improvements.
Camera Motion Graphs
(The Eurographics Association, 2014) Sanokho, Cunka Bassirou; Desoche, Clement; Merabti, Billal; Li, Tsai-yen; Christie, Marc; Vladlen Koltun and Eftychios Sifakis
This paper presents Camera Motion Graphs, a technique to easily and efficiently generate cinematographic sequences in real-time dynamic 3D environments. A camera motion graph consists of (i) pieces of original camera trajectories attached to one or multiple targets, (ii) generated continuous transitions between camera trajectories and (iii) transitions representing cuts between camera trajectories. Pieces of original camera trajectories are built by extracting camera motions from real movies using vision-based techniques, or relying on motion capture techniques using a virtual camera system. A transformation is proposed to recompute all the camera trajectories in a normalized representation, making camera paths easily adaptable to new 3D environments through a specific retargeting technique. The camera motion graph is then constructed by sampling all pairs of camera trajectories and evaluating the possibility and quality of continuous or cut transitions. Results illustrate the simplicity of the technique, its adaptability to different 3D environments and its efficiency.
Example-based Haze Removal with two-layer Gaussian Process Regressions
(The Eurographics Association, 2014) Fan, Xin; Gao, Renjie; Wang, Yi; John Keyser and Young J. Kim and Peter Wonka
Hazy images suffer from low visibility and contrast. Researchers have devoted great efforts to haze removal with the prior assumptions on observations in the past decade. However, these priors from observations can provide limited information for the restoration of high quality, and the assumptions are not always true for generic images in practice. On the other hand, visual data are increasing as the popularity of imaging devices. In this paper, we present a learning framework for haze removal based on two-layer Gaussian Process Regressions (GPR). By using training examples, the two-layer GPRs establish direct relationships from the input image to the depth-dependent transmission, and meanwhile learn local image priors to further improve the estimation. We also provide a method to collect training pairs for images of natural scenes. Both qualitative and quantitative comparisons on simulated and real-world hazy images demonstrate the effectiveness of the approach, especially when white or bright objects and heavy haze regions appear and existing dehazing methods may fail.
Instant Visualization of Secondary Structures of Molecular Models
(The Eurographics Association, 2015) Hermosilla, Pedro; Guallar, V.; Vinacua, Alvar; Vázquez, Pere-Pau; Katja Bühler and Lars Linsen and Nigel W. John
Molecular Dynamics simulations are of key importance in the drug design field. Among all possible representations commonly used to inspect these simulations, Ribbons has the advantage of giving the expert a good overview of the conformation of the molecule. Although several techniques have been previously proposed to render ribbons, all of them have limitations in terms of space or calculation time, making them not suitable for real-time interaction with simulation software. In this paper we present a novel adaptive method that generates ribbons in real-time, taking advantage of the tessellation shader. The result is a fast method that requires no precomputation, and that generates high quality shapes and shading.
Surfel Octrees: A New Scheme for Interactive Inspection of Anatomy Atlases in Client-Server Applications
(The Eurographics Association, 2015) Surinyac, Jordi; Brunet, Pere; Mateu Sbert and Jorge Lopez-Moreno
Nowadays, an increasing interest on tele-medicine and tele-diagnostic solutions can be observed, with client/server architectures for remote inspection of volume image-based medical data which are becoming more and more popular. The use of portable devices is gradually spreading due to their portability and easy maintenance. In this paper, we present an efficient data model for segmented volume models based on a hierarchical data structure of surfels per anatomical structure. Surfel Octrees are compact enough for transmission through networks with limited bandwidth, and provide good visual quality in the client devices at a limited footprint. Anatomy atlases are represented as octree forests, supporting local interaction in the client device and selection of groups of medical organs. After presenting the octree generation and interaction algorithms, we present several examples and discuss the interest of the proposed approach in low-end devices such as mobiles and tablets.
Improved Sparse Seeding for 3D Electrostatic Field Lines
(The Eurographics Association, 2015) Scharnowski, Katrin; Boblest, Sebastian; Ertl, Thomas; E. Bertini and J. Kennedy and E. Puppo
We present an improved seeding strategy for sparse visualization of electrostatic fields. By analyzing the curvature of the field lines, we extract points of extremal field strength between charges of different sign and use them to seed field lines, which consequently connect the corresponding charges. The resulting sparse representation can be seen as an extension to classic vector field topology depicting properties otherwise hidden. Finally, by applying our method to a synthetic data set, we show its benefits over previously published work.
Nonparametric Models for Uncertainty Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2013) Pöthkow, Kai; Hege, Hans-Christian; B. Preim, P. Rheingans, and H. Theisel
An uncertain (scalar, vector, tensor) field is usually perceived as a discrete random field with a priori unknown probability distributions. To compute derived probabilities, e.g. for the occurrence of certain features, an appropriate probabilistic model has to be selected. The majority of previous approaches in uncertainty visualization were restricted to Gaussian fields. In this paper we extend these approaches to nonparametric models, which are much more flexible, as they can represent various types of distributions, including multimodal and skewed ones. We present three examples of nonparametric representations: (a) empirical distributions, (b) histograms and (c) kernel density estimates (KDE). While the first is a direct representation of the ensemble data, the latter two use reconstructed probability density functions of continuous random variables. For KDE we propose an approach to compute valid consistent marginal distributions and to efficiently capture correlations using a principal component transformation. Furthermore, we use automatic bandwidth selection, obtaining a model for probabilistic local feature extraction. The methods are demonstrated by computing probabilities of level crossings, critical points and vortex cores in simulated biofluid dynamics and climate data.

Filters

Author

Subject

Date

Has files

Settings

Sort By

Results per page

Search Results