1.
Evangelos Kalogerakis, Derek Nowrouzezahrai, Patricio Simari, James McCrae, Aaron Hertzmann, Karan Singh
"Real-time line drawing for animated surfaces"
Conditionally accepted to ACM Transactions on Graphics (TOG) (under revision) [Technical Report CSRG-571, March 2008, Computer Science Department, © 2008]
Keywords: real-time curvature, real-time line drawing, precomputed curvature, data-driven curvature, data-driven differential surface attribute 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 predict curvatures and their derivatives in real-time, enabling real-time object-space rendering of suggestive contours and other such curves. This represents an orders-of-magnitude speed improvement over existing reliable methods for curvature and derivatives of curvature tensor estimation. Our learned model is also very compact, typically requiring a few MBs of storage. We demonstrate our method for various types of animated objects in a variety of non-photorealistic rendering styles. We also demonstrate advantages of Independent Components Analysis (ICA) over PCA for reducing the set of curvatures.
[animation dataset on the left by Chris Landreth ©]
"Real-time line drawing for animated surfaces"
Conditionally accepted to ACM Transactions on Graphics (TOG) (under revision) [Technical Report CSRG-571, March 2008, Computer Science Department, © 2008]
Keywords: real-time curvature, real-time line drawing, precomputed curvature, data-driven curvature, data-driven differential surface attribute 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 predict curvatures and their derivatives in real-time, enabling real-time object-space rendering of suggestive contours and other such curves. This represents an orders-of-magnitude speed improvement over existing reliable methods for curvature and derivatives of curvature tensor estimation. Our learned model is also very compact, typically requiring a few MBs of storage. We demonstrate our method for various types of animated objects in a variety of non-photorealistic rendering styles. We also demonstrate advantages of Independent Components Analysis (ICA) over PCA for reducing the set of curvatures.
[animation dataset on the left by Chris Landreth ©]
2.
Derek Nowrouzezahrai, Evangelos Kalogerakis, Patricio Simari, Eugene Fiume
"Shadowed Relighting of Dynamic Geometry with 1D BRDFs"
To appear in the 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...
"Shadowed Relighting of Dynamic Geometry with 1D BRDFs"
To appear in the 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...
3.
Derek Nowrouzezahrai, Patricio Simari, Evangelos Kalogerakis, Eugene Fiume
"Eigentransport for Efficient and Accurate All-Frequency Relighting"
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
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...
"Eigentransport for Efficient and Accurate All-Frequency Relighting"
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
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...
4.
Evangelos Kalogerakis, Patricio Simari, Derek Nowrouzezahrai, Karan
Singh
"Robust statistical estimation of curvature on discretized surfaces"
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, robust suggestive contour drawing, curvature of noisy irregular meshes
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...
"Robust statistical estimation of curvature on discretized surfaces"
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, robust suggestive contour drawing, curvature of noisy irregular meshes
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...
5.
Patricio Simari, Evangelos
Kalogerakis, Karan
Singh
"Folding meshes: Hierarchical mesh segmentation based on planar symmetry"
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
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...
"Folding meshes: Hierarchical mesh segmentation based on planar symmetry"
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
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...
6.
Evangelos Kalogerakis, Nektarios Moumoutzis, Stavros Christodoulakis
"Coupling ontologies with graphics content for Knowledge Driven Visualization"
Proceedings of the IEEE Virtual Reality Conference 2006 (IEEE VR '06), pp.43-50, Virginia, USA, 25-28 March 2006
Keywords: graphics ontologies, reasoning on virtual reality scenes, 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
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...
"Coupling ontologies with graphics content for Knowledge Driven Visualization"
Proceedings of the IEEE Virtual Reality Conference 2006 (IEEE VR '06), pp.43-50, Virginia, USA, 25-28 March 2006
Keywords: graphics ontologies, reasoning on virtual reality scenes, 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
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...