Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/43667
Title: Salient object detection via nonlocal diffusion tensor
Authors: Zhang, X
Xu, C
Sun, X
Baciu, G 
Keywords: Diffusion equation
Diffusion tensor
Nonlocal operator
Salient object detection
Issue Date: 2015
Publisher: World Scientific
Source: International journal of pattern recognition and artificial intelligence, 2015, v. 29, no. 7, 1555013 How to cite?
Journal: International journal of pattern recognition and artificial intelligence 
Abstract: In this paper, visual attention spreading is formulated as a nonlocal diffusion equation. Different from other diffusion-based methods, a nonlocal diffusion tensor is introduced to consider both the diffusion strength and the diffusion direction. With the help of diffusion tensor, along with the principle direction, the diffusion has been suppressed to preserve the dissimilarity between the foreground and background, while in other directions, the diffusion has been boosted to combine the similar regions and highlight the salient object as a whole. Through a two-stages diffusion, the final saliency maps are obtained. Extensive quantitative or visual comparisons are performed on three widely used benchmark datasets, i.e. MSRA-ASD, MSRA-B and PASCAL-1500 datasets. Experimental results demonstrate the superior performance of our method.
URI: http://hdl.handle.net/10397/43667
ISSN: 0218-0014
EISSN: 1793-6381
DOI: 10.1142/S0218001415550137
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