Video quality assessment for computer graphics applications

Abstract

Numerous current Computer Graphics methods produce video sequences as their outcome. The merit of these methods is often judged by assessing the quality of a set of results through lengthy user studies. We present a full-reference video quality metric geared specifically towards the requirements of Computer Graphics applications as a faster computational alternative to subjective evaluation. Our metric can compare a video pair with arbitrary dynamic ranges, and comprises a human visual system model for a wide range of luminance levels, that predicts distortion visibility through models of luminance adaptation, spatiotemporal contrast sensitivity and visual masking. We present applications of the proposed metric to quality prediction of HDR video compression and temporal tone mapping, comparison of different rendering approaches and qualities, and assessing the impact of variable frame rate to perceived quality.

DOI: 10.1145/1866158.1866187

Extracted Key Phrases

20 Figures and Tables

010202011201220132014201520162017
Citations per Year

68 Citations

Semantic Scholar estimates that this publication has 68 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Aydin2010VideoQA, title={Video quality assessment for computer graphics applications}, author={Tunç Ozan Aydin and Martin Cad{\'i}k and Karol Myszkowski and Hans-Peter Seidel}, journal={ACM Trans. Graph.}, year={2010}, volume={29}, pages={161:1-161:12} }