Natural motion statistics for no-reference video quality assessment

Abstract

We model the motion statistics of video sequences, towards the development of no-reference video quality indices that take into account spatial as well as temporal characteristics of video signals. Here we explore the temporal characteristics of undistorted as well as distorted IP video sequences; (distorted by varying levels of packet loss rate) as extracted from optical flow vectors. We present an algorithm for extracting motion statistics by computing independent components (ICs) from the optical flow field. We then model the extracted ICs, and show that they are more closely Laplacian distributed than the entire nondecomposed features. We also observe that the lower the video quality, the higher the root-mean-square (RMS) error difference between the maximum-likelihood Laplacian fits of the two extracted ICs of the flow vectors.