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Images Selection and Best Descriptor Combination for Multi-shot Person Re-identification

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Intelligent Interactive Multimedia Systems and Services 2017 (KES-IIMSS-18 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 76))

Abstract

To re-identify a person is to check if he/she has been already seen over a cameras network. Recently, re-identifying people over large public cameras networks has become a crucial task of great importance to ensure public security. The vision community has deeply studied this area of research. Most existing researches rely only on the spatial appearance information extracted from either one (single-shot) or multiple images (multi-shot) for each person. Actually, the real person re-identification framework is a multi-shot scenario. However, to efficiently model a person’s appearance and to select the most informative samples remain a challenging problem. In this work, an extensive comparison of descriptors of state of art associated to the proposed frame selection method is considered. Specifically, we evaluate the samples selection approach using different known descriptors. For fair comparisons, two standard datasets PRID 2011 and iLIDS-VID are used showing the effectiveness and advantages of the proposed method.

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Authors and Affiliations

  1. National School of Engineers of Sfax, Computer and Embedded Systems Laboratory, University of Sfax, 4.7 km Street of Soukra, 3038, Sfax, Tunisia

    Yousra Hadj Hassen, Kais Loukil, Tarek Ouni & Mohamed Jallouli

Authors
  1. Yousra Hadj Hassen
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  2. Kais Loukil
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  3. Tarek Ouni
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  4. Mohamed Jallouli
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Corresponding author

Correspondence to Yousra Hadj Hassen .

Editor information

Editors and Affiliations

  1. National Research Council of Italy (CNR-ICAR), Institute for High-Performance Computing and Networking, Naples, Italy

    Giuseppe De Pietro

  2. National Research Council of Italy (CNR-ICAR), Institute for High-Performance Computing and Networking, Naples, Italy

    Luigi Gallo

  3. Fern Barrow, Bournemouth University, Poole, Dorset, United Kingdom

    Robert J. Howlett

  4. University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

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Hadj Hassen, Y., Loukil, K., Ouni, T., Jallouli, M. (2018). Images Selection and Best Descriptor Combination for Multi-shot Person Re-identification. In: De Pietro, G., Gallo, L., Howlett, R., Jain, L. (eds) Intelligent Interactive Multimedia Systems and Services 2017. KES-IIMSS-18 2018. Smart Innovation, Systems and Technologies, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-319-59480-4_2

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  • DOI: https://doi.org/10.1007/978-3-319-59480-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59479-8

  • Online ISBN: 978-3-319-59480-4

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