Efficient motion weighted spatio-temporal video SSIM index

Recently, Seshadrinathan and Bovik proposed the Motion-based Video Integrity Evaluation (MOVIE) index for VQA. MOVIE utilized a multi-scale spatio-temporal Gabor filter bank to decompose the videos and to compute motion vectors. Apart from its psychovisual inspiration, MOVIE is an interesting option for VQA owing to its performance. However, the use of MOVIE in a practical setting may prove to be difficult owing to the presence of the multi-scale optical flow computation. In order to bridge the gap between the conceptual elegance of MOVIE and a practical VQA algorithm, we propose a new VQA algorithm the spatio-temporal video SSIM based on the essence of MOVIE. Spatio-temporal video SSIM utilizes motion information computed from a block-based motion-estimation algorithm and quality measures using a localized set of oriented spatio-temporal filters. In this paper we explain the algorithm and demonstrate its conceptual similarity to MOVIE; we explore its computational complexity and evaluate its performance on the popular VQEG dataset. We show that the proposed algorithm allows for efficient FR VQA without compromising on the performance while retaining the conceptual elegance of MOVIE.