The visible differences predictor: an algorithm for the assessment of image fidelity
Digital images and human vision
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Appearance-preserving simplification
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
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Proceedings of the 25th annual conference on Computer graphics and interactive techniques
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I3D '03 Proceedings of the 2003 symposium on Interactive 3D graphics
Level of Detail for 3D Graphics
Level of Detail for 3D Graphics
User-configurable automatic shader simplification
ACM SIGGRAPH 2005 Papers
GPU-based trimming and tessellation of NURBS and T-Spline surfaces
ACM SIGGRAPH 2005 Papers
Perceptually driven interactive geometry remeshing
I3D '06 Proceedings of the 2006 symposium on Interactive 3D graphics and games
Evaluation of a multiscale color model for visual difference prediction
ACM Transactions on Applied Perception (TAP)
Video quality assessment for computer graphics applications
ACM SIGGRAPH Asia 2010 papers
Perception of simplification artifacts for animated characters
Proceedings of the ACM SIGGRAPH Symposium on Applied Perception in Graphics and Visualization
Perception of visual artifacts in image-based rendering of façades
EGSR'11 Proceedings of the Twenty-second Eurographics conference on Rendering
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EGSR'10 Proceedings of the 21st Eurographics conference on Rendering
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Popping is a major source of visual artifacts in dynamic scenes. To alleviate or avoid it, usually some temporal smoothing scheme is employed or levels of detail are chosen conservatively based on geometric deviation measures. In this paper, we consider the actual perceptibility of popping artifacts and its prediction. We first discuss several issues affecting popping perception, pointing out its complexity. Introducing some simplifying assumptions, we then present a practical perceptually-motivated predictor for popping. It makes heavy use of a spatio-velocity color vision model and aggregates the model output in a novel and useful way. We demonstrate the predictor's application to concrete examples, and discuss a conducted user study which indicates the validity of our approach.