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International Conference on Intelligent Computing

ICIC 2017: Intelligent Computing Theories and Application pp 432–441Cite as

Methods for Eliminating the Complex Background of Pedestrian Images

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10361))

Abstract

In order to eliminate the complex background of pedestrian images in the re-identification task, this paper introduces grab-cut and co-segmentation algorithms to eliminate the complex background for the different pedestrian datasets. Specifically, we use grab-cut to handle small person dataset. For the bigger dataset, the designed co-segmentation algorithm which based on HSV color space is applied. Experimental results show that the proposed methods have a good effect.

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Acknowledgments

This work was supported by the grants of the National Science Foundation of China, Nos. 61472173, 61572447, 61373098, 61672382, 61472280, 61672203, 61402334, 61520106006, 31571364, U1611265, and 61532008, China Postdoctoral Science Foundation Grant, Nos. 2016M601646.

Author information

Authors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, Shanghai, 201804, China

    Di Wu, Si-Jia Zheng & Zhi-peng Li

  2. School of Information and Computer, Anhui Agricultural University, Hefei, Anhui, China

    You-hua Zhang

Authors
  1. Di Wu
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  2. Si-Jia Zheng
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  3. You-hua Zhang
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  4. Zhi-peng Li
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Corresponding author

Correspondence to Di Wu .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Politecnico di Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

  4. Indian Institute of Technology, Kanpur, India

    Phalguni Gupta

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Wu, D., Zheng, SJ., Zhang, Yh., Li, Zp. (2017). Methods for Eliminating the Complex Background of Pedestrian Images. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10361. Springer, Cham. https://doi.org/10.1007/978-3-319-63309-1_40

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  • DOI: https://doi.org/10.1007/978-3-319-63309-1_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63308-4

  • Online ISBN: 978-3-319-63309-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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