Salient Object Detection Based on Laplace Diffusion Models with Sink Points

WANG Baoyan; ZHANG Tie; WANG Xingang

doi:10.11999/JEIT161296

Volume 39 Issue 8

Aug. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(8): 1934-1941

WANG Baoyan, ZHANG Tie, WANG Xingang. Salient Object Detection Based on Laplace Diffusion Models with Sink Points[J]. Journal of Electronics & Information Technology, 2017, 39(8): 1934-1941. doi: 10.11999/JEIT161296

Citation:

WANG Baoyan, ZHANG Tie, WANG Xingang. Salient Object Detection Based on Laplace Diffusion Models with Sink Points[J]. Journal of Electronics & Information Technology, 2017, 39(8): 1934-1941. doi: 10.11999/JEIT161296

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Salient Object Detection Based on Laplace Diffusion Models with Sink Points

doi: 10.11999/JEIT161296

1.
(College of Information Science and Engineering, Northeastern University, Shenyang 110819, China)
2.
(College of Science, Northeastern University, Shenyang 110819, China)

Funds:

The National Natural Science Foundation of China (51475086), The Natural Science Foundation of Liaoning Province (2014020026)

Received Date: 2016-11-28
Rev Recd Date: 2017-04-25
Publish Date: 2017-08-19

Abstract

Abstract

Based on Laplace similarity metrics, corresponding diffusion-based saliency models are proposed according to different clusters (sparse or dense) of salient seeds in the two-stage detection, a diffusion-based two-stage complementary method for salient object detection is therefore investigated. Especially for the introduction of sink points in the second stage, saliency maps obtained by this proposed method can well restrain background parts, as well as become more robust with the change of control factor. Experiments show that different diffusion models will cause diversities of saliency diffusion degree when salient seeds are determined. In addition, the two-stage Laplace-based diffusion model with sink points is more effective and robust than other two-stage diffusion models. Meanwhile, the proposed algorithm is superior over the existing five state-of-the-art methods in terms of different metrics. This exactly shows that the similarity metrics method applied to image retrieval and classification is also available for salient objects detection.
- Object detection,
- Saliency,
- Sink points,
- Laplace matrix,
- Diffusion model

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References(28)

References

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