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Sim, Jae-Young
Visual Information Processing Lab (VIP Lab)
Research Interests
  • Image processing, computer vision, 3D visual processing, signal processing

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Spatiotemporal saliency detection for video sequences based on random walk with restart

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Title
Spatiotemporal saliency detection for video sequences based on random walk with restart
Author
Kim, HansangKim. YoungbaeSim, Jae-YoungKim, Chang-Su
Issue Date
2015-08
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE TRANSACTIONS ON IMAGE PROCESSING, v.24, no.8, pp.2552 - 2564
Abstract
A novel saliency detection algorithm for video sequences based on the random walk with restart (RWR) 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. Finally, we estimate the spatiotemporal saliency distribution by finding the steady-state distribution of the walker. The proposed algorithm detects foreground salient objects faithfully, while suppressing cluttered backgrounds effectively, by incorporating the spatial transition matrix and the temporal restarting distribution systematically. Experimental results on various video sequences demonstrate that the proposed algorithm outperforms conventional saliency detection algorithms qualitatively and quantitatively.
URI
https://scholarworks.unist.ac.kr/handle/201301/12765
URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7091884
DOI
10.1109/TIP.2015.2425544
ISSN
1057-7149
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