The visible differences predictor: an algorithm for the assessment of image fidelity
Digital images and human vision
A signal processing approach to fair surface design
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
A model of visual masking for computer graphics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Spectral compression of mesh geometry
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Perceptually Optimized 3D Graphics
IEEE Computer Graphics and Applications
Perceptually-Driven Simplification for Interactive Rendering
Proceedings of the 12th Eurographics Workshop on Rendering Techniques
Restricted delaunay triangulations and normal cycle
Proceedings of the nineteenth annual symposium on Computational geometry
Discrete Differential Error Metric for Surface Simplification
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
Anisotropic polygonal remeshing
ACM SIGGRAPH 2003 Papers
An Effective Feature-Preserving Mesh Simplification Scheme Based on Face Constriction
PG '01 Proceedings of the 9th Pacific Conference on Computer Graphics and Applications
ACM SIGGRAPH 2005 Papers
Predicting and Evaluating Saliency for Simplified Polygonal Models
ACM Transactions on Applied Perception (TAP)
Perceptually-motivated graphics, visualization and 3D displays
ACM SIGGRAPH 2010 Courses
Perception in graphics, visualization, virtual environments and animation
SIGGRAPH Asia 2011 Courses
Markov random fields for improving 3D mesh analysis and segmentation
EG 3DOR'08 Proceedings of the 1st Eurographics conference on 3D Object Retrieval
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3D models are subject to a wide variety of processing operations such as compression, simplification or watermarking, which introduce slight geometric modifications on the shape. The main issue is to maximize the compression/simplification ratio or the watermark strength while minimizing these visual degradations. However few algorithms exploit the human visual system to hide these degradations, while perceptual attributes could be quite relevant for this task. Particularly, the Masking Effect defines the fact that a signal can be masked by the presence of another signal with similar frequency or orientation. In this context we introduce the notion of roughness for a 3D mesh, as a local measure of geometric noise on the surface. Indeed, a textured (or rough) region is able to hide geometric distortions much better than a smooth one. Our measure is based on curvature analysis on local windows of the mesh and is independent of the resolution/connectivity of the object. An application to Visual Masking is presented and discussed.