Spatiotemporal Saliency Detection for Video Sequences Based on Random Walk With Restart
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Spatiotemporal Saliency Detection for Video Sequences Based on Random Walk With Restart
Abstract— Spatiotemporal Saliency Detection for Video Sequences Based on Random Walk With Restart. A novel saliency detection algorithm for video sequences based on the random walk with restart RWR < Final Year Projects 2016 > is proposed in this paper. We adopt RWR to detect spatially and temporally salient regions. More specifically, we first find a temporal saliency distribution using the features of motion distinctiveness, temporal consistency, and abrupt change. Among them, the motion distinctiveness is derived by comparing the motion profiles of image patches. Then, we employ the temporal saliency distribution as a restarting distribution of the random walker. In addition, we design the transition probability matrix for the walker using the spatial features of intensity, color, and compactness.
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