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Improving Person Re-identification by Background Subtraction Using Two-Stream Convolutional Networks

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Book cover Image Analysis and Recognition (ICIAR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11662))

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Abstract

The field of person re-identification is facing problems related to the variation of illumination and background scenes. In order to reduce the impact of those variations, we propose in this work a two-stream re-identification system based on a siamese network (S-CNN). The proposed system takes as input a pair of person images: the original image and the image without background. In the background subtraction step, a segmentation network (SEG-CNN) is used to detect the person body part and capture a complementary information. We experimentally prove that the combination of the two streams (images with and without background) improves the recognition rates. In the rank-1, the improvement is respectively of \(2\%\) and \(4\%\) for Market-1501 and DukeMTMC-reID datasets.

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Acknowledgement

This project is carried out under the MOBIDOC scheme, funded by the EU through the EMORI program and managed by the ANPR. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research.

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Authors and Affiliations

  1. Digital Research Center of Sfax, 3021, Sfax, Tunisia

    Mahmoud Ghorbel, Sourour Ammar, Yousri Kessentini & Mohamed Jmaiel

  2. MIRACL Laboratory, Sfax University, Sfax, Tunisia

    Sourour Ammar & Yousri Kessentini

  3. ReDCAD Laboratory, Sfax University, Sfax, Tunisia

    Mohamed Jmaiel

Authors
  1. Mahmoud Ghorbel
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  2. Sourour Ammar
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  3. Yousri Kessentini
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  4. Mohamed Jmaiel
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Corresponding authors

Correspondence to Mahmoud Ghorbel , Sourour Ammar , Yousri Kessentini or Mohamed Jmaiel .

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Editors and Affiliations

  1. University of Waterloo, Waterloo, ON, Canada

    Fakhri Karray

  2. University of Porto, Porto, Portugal

    Aurélio Campilho

  3. University of Waterloo, Waterloo, ON, Canada

    Alfred Yu

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Ghorbel, M., Ammar, S., Kessentini, Y., Jmaiel, M. (2019). Improving Person Re-identification by Background Subtraction Using Two-Stream Convolutional Networks. In: Karray, F., Campilho, A., Yu, A. (eds) Image Analysis and Recognition. ICIAR 2019. Lecture Notes in Computer Science(), vol 11662. Springer, Cham. https://doi.org/10.1007/978-3-030-27202-9_31

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  • DOI: https://doi.org/10.1007/978-3-030-27202-9_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27201-2

  • Online ISBN: 978-3-030-27202-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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