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ColorVideoVDP is a video and image quality metric that models spatial andtemporal aspects of vision, for both luminance and color. The metric is builton novel psychophysical models of chromatic spatiotemporal contrast sensitivityand cross-channel contrast masking. It accounts for the viewing conditions,geometric, and photometric characteristics of the display. It was trained topredict common video streaming distortions (e.g. video compression, rescaling,and transmission errors), and also 8 new distortion types related to AR/VRdisplays (e.g. light source and waveguide non-uniformities). To address thelatter application, we collected our novel XR-Display-Artifact-Video qualitydataset (XR-DAVID), comprised of 336 distorted videos. Extensive testing onXR-DAVID, as well as several datasets from the literature, indicate asignificant gain in prediction performance compared to existing metrics.ColorVideoVDP opens the doors to many novel applications which require thejoint automated spatiotemporal assessment of luminance and color distortions,including video streaming, display specification and design, visual comparisonof results, and perceptually-guided quality optimization.

ColorVideoVDP: A visual difference predictor for image, video and display distortions