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SDALF: Modeling Human Appearance with Symmetry-Driven Accumulation of Local Features

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Person Re-Identification

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

Abstract

In video surveillance, person re-identification (re-id) is probably the open challenge, when dealing with a camera network with non-overlapped fields of view. Re-id allows the association of different instances of the same person across different locations and time. A large number of approaches have emerged in the last 5 years, often proposing novel visual features specifically designed to highlight the most discriminant aspects of people, which are invariant to pose, scale and illumination. In this chapter, we follow this line, presenting a strategy with three important key-characteristics that differentiate it with respect to the state of the art: (1) a symmetry-driven method to automatically segment salient body parts, (2) an accumulation of features making the descriptor more robust to appearance variations, and (3) a person re-identification procedure casted as an image retrieval problem, which can be easily embedded into a multi-person tracking scenario, as the observation model.

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Notes

  1. 1.

    Code available at http://www2.cvl.isy.liu.se/~perfo/software/.

  2. 2.

    The following values have been computed using our non-optimized MATLAB code on a quad-core Intel Xeon E\(5440\), \(2.83\) GHz with \(30\) GB of RAM.

  3. 3.

    Available at http://users.soe.ucsc.edu/~dgray/VIPeR.v1.0.zip.

  4. 4.

    Available at http://www.liv.ic.unicamp.br/~wschwartz/datasets.html.

  5. 5.

    Available at http://www.lorisbazzani.info/code-datasets/caviar4reid/.

  6. 6.

    Available at http://homepages.inf.ed.ac.uk/rbf/CAVIARDATA1/.

  7. 7.

    For the sake of fairness, we use the code provided by the authors. For the metric ATA, we use the association threshold suggested by the authors (\(0.5\)).

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Author information

Authors and Affiliations

  1. Pattern Analysis & Computer Vision, Istituto Italiano di Tecnologia, Genova, Italy

    Loris Bazzani, Marco Cristani & Vittorio Murino

  2. University of Verona, Verona, Italy

    Marco Cristani & Vittorio Murino

Authors
  1. Loris Bazzani
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  2. Marco Cristani
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  3. Vittorio Murino
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Corresponding author

Correspondence to Loris Bazzani .

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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Bazzani, L., Cristani, M., Murino, V. (2014). SDALF: Modeling Human Appearance with Symmetry-Driven Accumulation of Local Features. 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_3

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  • DOI: https://doi.org/10.1007/978-1-4471-6296-4_3

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  • Online ISBN: 978-1-4471-6296-4

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