9.
Evangelos Kalogerakis, Derek Nowrouzezahrai, Patricio Simari, James McCrae, Aaron Hertzmann, Karan Singh
"Data-driven curvature for real-time line drawing of dynamic scenes" [PAPER] [VIDEO]
ACM Transactions on Graphics journal, Volume 28, Issue 1, January 2009 - To be also presented in SIGGRAPH 2009, New Orleans, USA, August 3 - 9, 2009
Keywords: real-time curvature, real-time line drawing, precomputed curvature, data-driven curvature, data-driven differential surface attribute estimation, real-time derivatives of curvature estimation
Abstract: This paper presents a method for real-time line drawing of deforming objects. Object-space line drawing algorithms for many types of curves, including suggestive contours, highlights, ridges and valleys, rely on surface curvature and curvature derivatives. Unfortunately, these curvatures and their derivatives cannot be computed in real-time for animated, deforming objects. In a preprocessing step, our method learns the mapping from a low-dimensional set of animation parameters (e.g., joint angles) to surface curvatures for a deforming 3D mesh. The learned model can then accurately and efficiently predict curvatures and their derivatives, enabling real-time object-space rendering of suggestive contours and other such curves. This represents an order-of-magnitude speed-up over the fastest existing algorithm capable of estimating curvatures and their derivatives accurately enough for many different types of line drawings. The learned model can generalize to novel animation sequences, and is also very compact, typically requiring a few megabytes of storage at run-time. We demonstrate our method for various types of animated objects, including skeleton-based characters, cloth simulation and blend-shape facial animation, using a variety of non-photorealistic rendering styles.An important component of our system is the use of dimensionality reduction for differential mesh data. We show that Independent Component Analysis (ICA) yields localized basis functions, and gives superior generalization performance to that of Principal Component Analysis (PCA).
8.
Patricio Simari, Derek Nowrouzezahrai, Evangelos Kalogerakis, Karan Singh
"Multi-objective shape segmentation and labeling" [PAPER] [VIDEO]
Special Issue of Computer Graphics Forum journal - To be also presented in Eurographics/ACM Siggraph Symposium of Geometry Processing 2009, Berlin, Germany, July 15 - 17
Keywords: mesh segmentation, mesh part labeling, semantic segmentation, multi-objective segmentation
Abstract: Shape segmentations designed for different applications show significant variation in the composition of their parts. In this paper, we introduce the segmentation and labeling of shape based on the simultaneous optimization of multiple heterogenous objectives that capture application-specific segmentation criteria. We present a number of efficient objective functions that capture useful shape adjectives (compact, flat, narrow, perpendicular, etc.) Segmentation descriptions within our framework combine multiple such objective functions with optional labels to define each part. The optimization problem is simplified by proposing weighted Voronoi partitioning as a compact and continuous parametrization of spatially embedded shape segmentations. Separation of spatially close but geodesically distant parts is made possible using multi-dimensional scaling prior to Voronoi partitioning. Optimization begins with an initial segmentation found using the centroids of a k-means clustering of surface elements. This partition is automatically labeled to optimize heterogeneous part objectives and the Voronoi centers and their weights optimized using Generalized Pattern Search. We illustrate our framework using several diverse segmentation applications: consistent segmentations with semantic labels, bounding volume hierarchies for path tracing, and automatic rig and clothing transfer between animation characters.
[animation dataset by Joel Anderson ©]7.
Derek Nowrouzezahrai, Evangelos Kalogerakis, Eugene Fiume
"Shadowing Dynamic Scenes with Arbitrary BRDFs" [PAPER] [VIDEO]
Special Issue of Computer Graphics Forum journal, Volume 28, Issue 2 (April 2009), pp.249-258 - also presented in Eurographics 2009, Munich, Germany, March 30 - April 3
Keywords: precomputed radiance transfer for dynamic/deforming scenes, data-driven PRT, real-time PRT, real-time arbitrary BRDF shading, visibility learning
Abstract: We present a real-time relighting and shadowing method for dynamic scenes with varying lighting, view and BRDFs. Our approach is based on a compact representation of reflectance data that allows for changing the BRDF at run-time and a data-driven method for accurately synthesizing self-shadows on articulated and deformable geometries. Unlike previous self-shadowing approaches, we do not rely on local blocking heuristics. We do not fit a model to the BRDF-weighted visibility, but rather only to the visibility that changes during animation. In this manner, our model is more compact than previous techniques and requires less computation both during fitting and at run-time. Our reflectance product operators can re-integrate arbitrary low-frequency view-dependent BRDF effects on-the-fly and are compatible with all previous dynamic visibility generation techniques as well as our own data-driven visibility model. We apply our reflectance product operators to three different visibility generation models, and our data-driven model can achieve framerates well over 300Hz.
6.
Evangelos Kalogerakis, Derek Nowrouzezahrai, Patricio Simari, Karan Singh
"Extracting lines of curvature from noisy point clouds" [PAPER]
Computer-Aided Design journal 2009, Special Issue on Point-Based Computational Techniques, Volume 41, Number 4 (April 2009), pp. 282-292
Keywords: lines of curvature, robust curvature estimation, point cloud denoising, outlier rejection, quad mesh construction
Abstract: We present a robust framework for extracting lines of curvature from point clouds. First, we show a novel approach to denoising the input point cloud using robust statistical estimates of surface normal and curvature which automatically rejects outliers and corrects points by energy minimization. Then the lines of curvature are constructed on the point cloud with controllable density. Our approach is applicable to surfaces of arbitrary genus, with or without boundaries, and is statistically robust to noise and outliers while preserving sharp surface features. We show our approach to be e ective over a range of synthetic and real-world input datasets with varying amounts of noise and outliers. The extraction of curvature information can benefit many applications in CAD, computer vision and graphics for point cloud shape analysis, recognition and segmentation. Here, we show the possibility of using the lines of curvature for feature-preserving mesh construction directly from noisy point clouds.
5.
"Shadowed Relighting of Dynamic Geometry with 1D BRDFs" [VIDEO]
Short Paper, Proceedings of the Eurographics 2008 conference, Crete, Greece, April 14-18 2008
Keywords: dynamic radiance transfer, data driven PRT, real-time PRT, real-time 1D BRDF shading, real-time Phong shading, visibility learning
Abstract: We present a method for synthesizing the dynamic self-occlusion of an articulating character in real-time (> 170Hz) while incorporating reflection effects from 1D BRDFs under dynamic lighting and view conditions. We introduce and derive a general operator form for convolving spherical harmonics (SH) occlusion vectors with arbitrary 1D BRDF kernels. This operator, coupled with a compact linear model for predicting SH occlusion over articulating meshes, segments the BRDF and visibility terms of the direct illumination integral. We illustrate our results on a thin-membrane translucency model and the normalized Phong BRDF.
4.
"Eigentransport for Efficient and Accurate All-Frequency Relighting" [PAPER]
Proceedings of the ACM Graphite 2007 conference, Perth, Australia, Dec 2-4 2007 - Best Paper Award
Keywords: geometry dependent basis for PRT, real time all-frequency relighting, principal component analysis on PRT data
Abstract: We present a method for creating a geometry-dependent basis for precomputed radiance transfer. Unlike previous PRT bases, ours is derived from principal component analysis of the sampled transport functions at each vertex. It allows for efficient evaluation of shading, has low memory requirements and produces accurate results with few coefficients. We are able to capture all-frequency effects from both distant and near-field dynamic lighting in real-time and present a simple rotation scheme. Reconstruction of the final shading becomes a low-order dot product and is performed on the GPU.
3.
"Robust statistical estimation of curvature on discretized surfaces" [PAPER]
Proceedings of the Eurographics/ACM Siggraph Symposium on Geometry Processing (SGP '07), pp. 13-22, Barcelona, Spain, July 4-6 2007
Keywords: robust curvature, statistical estimation of surface derivatives, maximum likelihood estimates of curvature, surface normal correction, curvature of noisy irregular meshes, robust derivatives of curvature
Abstract: A robust statistics approach to curvature estimation on discretely sampled surfaces, namely polygon meshes and point clouds, is presented. The method exhibits accuracy, stability and consistency even for noisy, non-uniformly sampled surfaces with irregular configurations. Within an M-estimation framework, the algorithm is able to reject noise and structured outliers by sampling normal variations in an adaptively reweighted neighborhood around each point. The algorithm can be used to reliably derive higher order differential attributes and even correct noisy surface normals while preserving the fine features of the normal and curvature field. The approach is compared with state-of-the-art curvature estimation methods and shown to improve accuracy by up to an order of magnitude across ground truth test surfaces under varying tessellation densities and types as well as increasing degrees of noise. Finally, the benefits of a robust statistical estimation of curvature are illustrated by applying it to the popular applications of mesh segmentation and suggestive contour rendering.
2.
"Folding meshes: Hierarchical mesh segmentation based on planar symmetry" [PAPER]
Proceedings of the Eurographics/ACM Siggraph Symposium on Geometry Processing (SGP '06), pp. 111-119, Cagliari, Italy, June 26-28, 2006
Keywords: symmetry detection, symmetry-based segmentation, mesh folding, mesh compression, planar symmetry detection
Abstract: Meshes representing real world objects, both artist-created and scanned, contain a high level of redundancy due to (possibly approximate) planar reflection symmetries, either global or localized to different subregions. An algorithm is presented for detecting such symmetries and segmenting the mesh into the symmetric and remaining regions. The method, inspired by techniques in Computer Vision, has foundations in robust statistics and is resilient to structured outliers which are present in the form of the non symmetric regions of the data. Also introduced is an application of the method: the folding tree data structure. The structure encodes the non redundant regions of the original mesh as well as the reflection planes and is created by the recursive application of the detection method. This structure can then be unfolded to recover the original shape. Applications include mesh compression, repair as well as mesh processing acceleration by limiting computation to non redundant regions and propagation of results.
1.
"Coupling ontologies with graphics content for Knowledge Driven Visualization" [PAPER]
Proceedings of the IEEE Virtual Reality Conference 2006 (IEEE VR '06), pp.43-50, Virginia, USA, 25-28 March 2006
Keywords: graphics ontologies, domain-specific knowledge representation for virtual and augmented reality, semantic visualization, semantic quering on 3D scenes, semantic personalization for 3D applications, visualization-aided decision making, interoperable 3D standards and formats, reasoning for virtual reality scenes
Abstract: A great challenge in information visualization today is to provide models and software that effectively integrate the graphics content of scenes with domain-specific knowledge so that the users can effectively query, interpret, personalize and manipulate the visualized information. Moreover, it is important that the intelligent visualization applications are interoperable in the semantic web environment and thus, require that the models and software supporting them integrate state-of-the-art international standards for knowledge representation, graphics and multimedia. In this paper, we present a model, a methodology and a software framework for the semantic web (Intelligent 3D Visualization Platform - I3DVP) for the development of interoperable intelligent visualization applications that support the coupling of graphics and virtual reality scenes with domain knowledge of different domains. The graphics content and the semantics of the scenes are married into a consistent and cohesive ontological model while at the same time knowledge-based techniques for the querying, manipulation, and semantic personalization of the scenes are introduced. We also provide methods for knowledge driven information visualization and visualization-aided decision making based on inference by reasoning.