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Two-Stage Filtering Scheme for Sparse Representation Based Interest Point Matching for Person Re-identification

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9386))

Abstract

The objective of this paper is to study Interest Points (IP) filtering in video-based human re-identification tasks. The problem is that having a large number of IPs to describe person, Re-identification grows into a much time consuming task and IPs become redundant. In this context, we propose a Two-Stage filtering step. The first stage reduces the number of IP to be matched and the second ignores weak matched IPs participating in the re-identification decision. The proposed approach is based on the supervision of SVM, learned on training dataset. Our approach is evaluated on the dataset PRID-2011 and results show that it is fast and compare favorably with the state of the art.

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Authors and Affiliations

  1. Institut Mines-Telecom, Telecom SudParis: CEA Saclay Nano-Innov, 91191, Gif sur Yvette Cedex, France

    Mohamed Ibn Khedher & Mounim A. El Yacoubi

Authors
  1. Mohamed Ibn Khedher
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  2. Mounim A. El Yacoubi
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Corresponding author

Correspondence to Mohamed Ibn Khedher .

Editor information

Editors and Affiliations

  1. Dipartimento di Matematica e Informatica, Università di Catania, Catania, Catania, Italy

    Sebastiano Battiato

  2. Arcueil CX, France

    Jacques Blanc-Talon

  3. Catania, Italy

    Giovanni Gallo

  4. Gent, Belgium

    Wilfried Philips

  5. CSIRO, Sydney, New South Wales, Australia

    Dan Popescu

  6. Vision Lab., University of Antwerp, Antwerpen, Belgium

    Paul Scheunders

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© 2015 Springer International Publishing Switzerland

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Khedher, M.I., El Yacoubi, M.A. (2015). Two-Stage Filtering Scheme for Sparse Representation Based Interest Point Matching for Person Re-identification. In: Battiato, S., Blanc-Talon, J., Gallo, G., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2015. Lecture Notes in Computer Science(), vol 9386. Springer, Cham. https://doi.org/10.1007/978-3-319-25903-1_30

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  • DOI: https://doi.org/10.1007/978-3-319-25903-1_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25902-4

  • Online ISBN: 978-3-319-25903-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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