SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Surface simplification using quadric error metrics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Simplifying polygonal models using successive mappings
VIS '97 Proceedings of the 8th conference on Visualization '97
Appearance-preserving simplification
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Simplifying surfaces with color and texture using quadric error metrics
Proceedings of the conference on Visualization '98
Fast and memory efficient polygonal simplification
Proceedings of the conference on Visualization '98
New quadric metric for simplifiying meshes with appearance attributes
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Spectral compression of mesh geometry
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
ACM Transactions on Graphics (TOG)
Visibility-guided simplification
Proceedings of the conference on Visualization '02
Perceptually guided simplification of lit, textured meshes
I3D '03 Proceedings of the 2003 symposium on Interactive 3D graphics
Viewpoint Selection using Viewpoint Entropy
VMV '01 Proceedings of the Vision Modeling and Visualization Conference 2001
Perceptually-Driven Simplification for Interactive Rendering
Proceedings of the 12th Eurographics Workshop on Rendering Techniques
Refinement criteria based on f-divergences
EGRW '03 Proceedings of the 14th Eurographics workshop on Rendering
Relative information of type s, Csiszár's f-divergence, and information inequalities
Information Sciences—Informatics and Computer Science: An International Journal
ACM SIGGRAPH 2005 Papers
Streaming Simplification of Tetrahedral Meshes
IEEE Transactions on Visualization and Computer Graphics
A mesh optimization algorithm based on neural networks
Information Sciences: an International Journal
A unified information-theoretic framework for viewpoint selection and mesh saliency
ACM Transactions on Applied Perception (TAP)
A comparative study of acceleration techniques for geometric visualization
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
Techniques for computing viewpoint entropy of a 3d scene
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
Viewpoint quality: measures and applications
Computational Aesthetics'05 Proceedings of the First Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
The Pólya information divergence
Information Sciences: an International Journal
Divergence statistics for testing uniform association in cross-classifications
Information Sciences: an International Journal
A neural network model to develop urban acupuncture
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Technical Section: View-dependent pruning for real-time rendering of trees
Computers and Graphics
An application of a self-organizing model to the design of urban transport networks
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Evolutionary neural networks for practical applications
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We propose a new viewpoint-based simplification method for polygonal meshes, driven by several f-divergences such as Kullback-Leibler, Hellinger and Chi-Square. These distances are a measure of discrimination between probability distributions. The Kullback-Leibler distance between the projected and the actual area distributions of the polygons in the scene already has been used as a measure of viewpoint quality. In this paper, we use the variation in those viewpoint distances to determine the error introduced by an edge collapse. We apply the best half-edge collapse as a decimation criterion. The approximations produced by our method are close to the original model in terms of both visual and geometric criteria. Unlike many pure visibility-driven methods, our new approach does not completely remove hidden interiors in order to increase the visual quality of the simplified models. This makes our approach more suitable for applications which require exact geometry tolerance but also require high visual quality.