Motion-based perceptual quality assessment of video

There is a great deal of interest in methods to assess the perceptual quality of a video sequence in a full reference framework. Motion plays an important role in human perception of video and videos suffer from several artifacts that have to deal with inaccuracies in the representation of motion in the test video compared to the reference. However, existing algorithms to measure video quality focus primarily on capturing spatial artifacts in the video signal, and are inadequate at modeling motion perception and capturing temporal artifacts in videos. We present an objective, full reference video quality index known as the MOtion-based Video Integrity Evaluation (MOVIE) index that integrates both spatial and temporal aspects of distortion assessment. MOVIE explicitly uses motion information from the reference video and evaluates the quality of the test video along the motion trajectories of the reference video. The performance of MOVIE is evaluated using the VQEG FR-TV Phase I dataset and MOVIE is shown to be competitive with, and even out-perform, existing video quality assessment systems.