• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Salient Object Detection via Multiple Random Walks

Vol. 10, No. 4, April 29, 2016
10.3837/tiis.2016.04.014, Download Paper (Free):


In this paper, we propose a novel saliency detection framework via multiple random walks (MRW) which simulate multiple agents on a graph simultaneously. In the MRW system, two agents, which represent the seeds of background and foreground, traverse the graph according to a transition matrix, and interact with each other to achieve a state of equilibrium. The proposed algorithm is divided into three steps. First, an initial segmentation is performed to partition an input image into homogeneous regions (i.e., superpixels) for saliency computation. Based on the regions of image, we construct a graph that the nodes correspond to the superpixels in the image, and the edges between neighboring nodes represent the similarities of the corresponding superpixels. Second, to generate the seeds of background, we first filter out one of the four boundaries that most unlikely belong to the background. The superpixels on each of the three remaining sides of the image will be labeled as the seeds of background. To generate the seeds of foreground, we utilize the center prior that foreground objects tend to appear near the image center. In last step, the seeds of foreground and background are treated as two different agents in multiple random walkers to complete the process of salient object detection. Experimental results on three benchmark databases demonstrate the proposed method performs well when it against the state-of-the-art methods in terms of accuracy and robustness.


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Cite this article

[IEEE Style]
J. Zhai, J. Zhou, Y. Ren and Z. Wang, "Salient Object Detection via Multiple Random Walks," KSII Transactions on Internet and Information Systems, vol. 10, no. 4, pp. 1712-1731, 2016. DOI: 10.3837/tiis.2016.04.014.

[ACM Style]
Jiyou Zhai, Jingbo Zhou, Yongfeng Ren, and Zhijian Wang. 2016. Salient Object Detection via Multiple Random Walks. KSII Transactions on Internet and Information Systems, 10, 4, (2016), 1712-1731. DOI: 10.3837/tiis.2016.04.014.

[BibTeX Style]
@article{tiis:21080, title="Salient Object Detection via Multiple Random Walks", author="Jiyou Zhai and Jingbo Zhou and Yongfeng Ren and Zhijian Wang and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2016.04.014}, volume={10}, number={4}, year="2016", month={April}, pages={1712-1731}}