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Stereo Saliency Analysis Based on Disparity Influence and Spatial Dissimilarity

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Book cover Advances in Multimedia Information Processing – PCM 2017 (PCM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10736))

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Abstract

This paper presents a simple approach for detecting salient regions in stereo images. The approach computes saliency by considering three factors: disparity influence, central bias and spatial dissimilarity. Firstly, an image is split into equal-sized patches to be down-sampled. Next, disparity influence is estimated based on the disparity map. Besides, central bias value is assigned to every patch and spatial dissimilarity is measured between patches in reduced dimensional space. Thereafter, the product of all factors extracted from the image is computed. Finally, through a process of normalization, the saliency map is obtained. In the experiments four state-of-the-art methods are used for comparison with PSU stereo saliency benchmark dataset (SSB). The experimental results show that our method has better performance than the others for stereo salient region detection.

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Acknowledgments

This research is partially sponsored by National Natural Science Foundation of China [61370113, 61672070, 91546111, 61572004]; and Beijing Municipal Natural Science Foundation [4152005, 4152006, 4162058]; the Science and Technology Program of Tianjin [15YFXQGX0050]; the Science and technology planning project of Qinghai Province [2016-ZJ-Y04]; the Beijing Municipal Education Commission Science and Technology Program [KZ201610005009, KM201610005022, KM201510005015].

Author information

Authors and Affiliations

  1. Faculty of Information Technology, Beijing University of Technology, Beijing, China

    Lijuan Duan, Fangfang Liang, Wei Ma & Shuo Qiu

  2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, College of Computer Science and Technology, Beijing University of Technology, Beijing, 100124, China

    Lijuan Duan

  3. Beijing Key Laboratory of Trusted Computing, Beijing, 100124, China

    Fangfang Liang, Wei Ma & Shuo Qiu

  4. National Engineering Laboratory for Critical Technologies of Information Security Classified Protection, Beijing, 100124, China

    Lijuan Duan, Fangfang Liang, Wei Ma & Shuo Qiu

Authors
  1. Lijuan Duan
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  2. Fangfang Liang
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  3. Wei Ma
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  4. Shuo Qiu
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Corresponding author

Correspondence to Wei Ma .

Editor information

Editors and Affiliations

  1. University of Electronic Science and Technology of China, Chengdu, China

    Bing Zeng

  2. University of Chinese Academy of Sciences, Beijing, China

    Qingming Huang

  3. University of Ottawa, Ottawa, Ontario, Canada

    Abdulmotaleb El Saddik

  4. University of Electronic Science and Technology of China, Chengdu, China

    Hongliang Li

  5. Chinese Academy of Sciences, Beijing, China

    Shuqiang Jiang

  6. Harbin Institute of Technology, Harbin, China

    Xiaopeng Fan

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Duan, L., Liang, F., Ma, W., Qiu, S. (2018). Stereo Saliency Analysis Based on Disparity Influence and Spatial Dissimilarity. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10736. Springer, Cham. https://doi.org/10.1007/978-3-319-77383-4_25

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  • DOI: https://doi.org/10.1007/978-3-319-77383-4_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77382-7

  • Online ISBN: 978-3-319-77383-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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