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Group Association: Assisting Re-identification by Visual Context

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Person Re-Identification

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

In a crowded public space, people often walk in groups, either with people they know or with strangers. Associating a group of people over space and time can assist understanding an individual’s behaviours as it provides vital visual context for matching individuals within the group. This seems to be an ‘easier’ task compared with person re-identification due to the availability of more and richer visual content in associating a group; however, solving this problem turns out to be rather challenging because a group of people can be highly non-rigid with changing relative position of people within the group and severe self-occlusions. In this work, the problem of matching/associating groups of people over large space and time gaps captured in multiple non-overlapping camera views is addressed. Specifically, a novel people group representation and a group matching algorithm are proposed. The former addresses changes in the relative positions of people in a group and the latter uses the proposed group descriptors for measuring the similarity between two candidate images. Based on group matching, we further formulate a method for matching individual person using the group description as visual context. These methods are validated using the 2008 i-LIDS Multiple-Camera Tracking Scenario (MCTS) dataset on multiple camera views from a busy airport arrival hall.

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Notes

  1. 1.

    This step is omitted when continuous image sequences are not available.

  2. 2.

    A foreground block is defined as an image block with more than 70 % pixels being foreground.

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Author information

Authors and Affiliations

  1. Sun Yat-sen University, Guangzhou, China

    Wei-Shi Zheng

  2. Queen Mary University of London, London, UK

    Shaogang Gong

  3. Queen Mary University of London, London, UK

    Tao Xiang

Authors
  1. Wei-Shi Zheng
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  2. Shaogang Gong
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  3. Tao Xiang
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Corresponding author

Correspondence to Wei-Shi Zheng .

Editor information

Editors and Affiliations

  1. Queen Mary University, London, United Kingdom

    Shaogang Gong

  2. University of Verona, Italy

    Marco Cristani

  3. National University of Singapore, Singapore

    Shuicheng Yan

  4. The Chinese University of Hong Kong, Shatin, Hong Kong SAR

    Chen Change Loy

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© 2014 Springer-Verlag London

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Zheng, WS., Gong, S., Xiang, T. (2014). Group Association: Assisting Re-identification by Visual Context. In: Gong, S., Cristani, M., Yan, S., Loy, C. (eds) Person Re-Identification. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-6296-4_9

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  • DOI: https://doi.org/10.1007/978-1-4471-6296-4_9

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-6295-7

  • Online ISBN: 978-1-4471-6296-4

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