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Salient Object Detection Using Window Mask Transferring with Multi-layer Background Contrast

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Computer Vision -- ACCV 2014 (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9005))

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Abstract

In this paper, we present a novel framework to incorporate bottom-up features and top-down guidance to identify salient objects based on two ideas. The first one automatically encodes object location prior to predict visual saliency without the requirement of center-biased assumption, while the second one estimates image saliency using contrast with respect to background regions. The proposed framework consists of the following three basic steps: In the top-down process, we create a specific location saliency map (SLSM), which can be identified by a set of overlapping windows likely to cover salient objects. The binary segmentation masks of training windows are treated as high-level knowledge to be transferred to the test image windows, which may share visual similarity with training windows. In the bottom-up process, a multi-layer segmentation framework is employed, which is able to provide vast robust background candidate regions specified by SLSM. Then the background contrast saliency map (BCSM) is computed based on low-level image stimuli features. SLSM and BCSM are finally integrated to a pixel-accurate saliency map. Extensive experiments show that our approach achieves the state-of-the-art results over MSRA 1000 and SED datasets.

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Acknowledgement

The authors would like to thank all the anonymous reviewers valuable comments. We would like to thank Prof. Liang Zhou for his valuable comments to improve the readability of the whole paper. This work was supported by NSFC 61201165, 61271240, 61401228, 61403350, PAPD and NY213067.

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Authors and Affiliations

  1. College of Telecommunication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, People’s Republic of China

    Quan Zhou, Shu Cai & Baoyu Zheng

  2. Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, USA

    Shaojun Zhu

Authors
  1. Quan Zhou
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  2. Shu Cai
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  3. Shaojun Zhu
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  4. Baoyu Zheng
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Corresponding author

Correspondence to Quan Zhou .

Editor information

Editors and Affiliations

  1. Technische Universität München, Garching, Bayern, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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Zhou, Q., Cai, S., Zhu, S., Zheng, B. (2015). Salient Object Detection Using Window Mask Transferring with Multi-layer Background Contrast. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9005. Springer, Cham. https://doi.org/10.1007/978-3-319-16811-1_15

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  • DOI: https://doi.org/10.1007/978-3-319-16811-1_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16810-4

  • Online ISBN: 978-3-319-16811-1

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