Compressed-Domain Correlates of Fixations in Video
Sayed Hossein Khatoonabadi, Ivan V. Bajić, Yufeng Shan · 2014
In this paper we present two compressed-domain features that are highly indicative of saliency in natural video. Their potential to predict saliency is demonstrated by comparing their statistics around human fixation points in a number of videos against the control points selected randomly away from fixations. Using these features, we construct a simple and effective saliency estimation method for compressed video, which utilizes only motion vectors, block coding modes and coded residuals from the bitstream, with partial decoding. The proposed algorithm has been extensively tested on two ground truth datasets using several accuracy metrics. The results indicate its superior performance over several state-of-the-art compressed-domain and pixel-domain algorithms for saliency estimation.