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Person Re-identification Using Appearance Classification

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6754))

Abstract

In this paper, we present a person re-identification method based on appearance classification. It consists a human silhouette comparison by characterizing and classification of a persons appearance (the front and the back appearance) using the geometric distance between the detected head of person and the camera. The combination of head detector with an orthogonal iteration algorithm to help head pose estimation and appearance classification is the novelty of our work. In this way, the is achieved robustness against viewpoint, illumination and clothes appearance changes. Our approach uses matching of interest-points descriptors based on fast cross-bin metric. The approach applies to situations where the number of people varies continuously, considering multiple images for each individual.

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Aziz, KE., Merad, D., Fertil, B. (2011). Person Re-identification Using Appearance Classification. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21596-4_18

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  • DOI: https://doi.org/10.1007/978-3-642-21596-4_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21595-7

  • Online ISBN: 978-3-642-21596-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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