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Proceedings Paper

Spatiotemporal saliency detection using border connectivity
Author(s): Tongbao Wu; Zhi Liu; Junhao Li
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Paper Abstract

This paper proposes a border connectivity-based spatiotemporal saliency model for videos with complicated motion and complex scenes. Based on the superpixel segmentation results of video frames, feature extraction is performed to obtain the three features, including motion orientation histogram, motion amplitude histogram and color histogram. Then the border connectivity is exploited to evaluate the importance of three features for distance fusion. Finally the background weighted contrast and saliency optimization are utilized to generate superpixel-level spatiotemporal saliency maps. Experimental results on a public benchmark dataset demonstrate that the proposed model outperforms the state-of-the- art saliency models on saliency detection performance.

Paper Details

Date Published: 29 August 2016
PDF: 6 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003344 (29 August 2016); doi: 10.1117/12.2244867
Show Author Affiliations
Tongbao Wu, Shanghai Univ. (China)
Zhi Liu, Shanghai Univ. (China)
Junhao Li, Shanghai Univ. (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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