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One-Shot Person Re-identification with a Consumer Depth Camera

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Person Re-Identification

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

Abstract

In this chapter, we propose a comparison between two techniques for one-shot person re-identification from soft biometric cues. One is based upon a descriptor composed of features provided by a skeleton estimation algorithm; the other compares body shapes in terms of whole point clouds. This second approach relies on a novel technique we propose to warp the subject’s point cloud to a standard pose, which allows to disregard the problem of the different poses a person can assume. This technique is also used for composing 3D models which are then used at testing time for matching unseen point clouds. We test the proposed approaches on an existing RGB-D re-identification dataset and on the newly built BIWI RGBD-ID dataset. This dataset provides sequences of RGB, depth, and skeleton data for 50 people in two different scenarios and it has been made publicly available to foster advancement in this new research branch.

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Notes

  1. 1.

    The BIWI RGBD-ID dataset can be downloaded at: http://robotics.dei.unipd.it/reid.

  2. 2.

    Microsoft’s SDK provides a flag for every joint stating if it is tracked, inferred, or not tracked.

  3. 3.

    It is worth noting that all the links belonging to the torso have the same orientation, as the hip center.

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Acknowledgments

The authors would like to thank all the people at the BIWI laboratory of ETH Zurich who took part in the BIWI RGBD-ID dataset.

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Authors and Affiliations

  1. Intelligent Autonomous Systems Laboratory, University of Padua, Via Gradenigo 6a, 35131, Padua, Italy

    Matteo Munaro, Alberto Basso & Emanuele Menegatti

  2. Computer Vision Laboratory, ETH Zurich, Sternwartstrasse 7, 8092, Zurich, Switzerland

    Andrea Fossati & Luc Van Gool

Authors
  1. Matteo Munaro
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  2. Andrea Fossati
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  3. Alberto Basso
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  4. Emanuele Menegatti
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  5. Luc Van Gool
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Corresponding author

Correspondence to Matteo Munaro .

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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Munaro, M., Fossati, A., Basso, A., Menegatti, E., Van Gool, L. (2014). One-Shot Person Re-identification with a Consumer Depth Camera. 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_8

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  • DOI: https://doi.org/10.1007/978-1-4471-6296-4_8

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  • Print ISBN: 978-1-4471-6295-7

  • Online ISBN: 978-1-4471-6296-4

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