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People Re-identification by Graph Kernels Methods

  • Conference paper
Graph-Based Representations in Pattern Recognition (GbRPR 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6658))

Abstract

People re-identification using single or multiple camera acquisitions constitutes a major challenge in visual surveillance analysis. The main application of this research field consists to reacquire a person of interest in different non-overlapping locations over different camera views. This paper present an original solution to this problem based on a graph description of each person. In particular, a recently proposed graph kernel is used to apply Principal Component Analysis (PCA) to the graph domain. The method has been experimentally tested on two video sequences from the PETS2009 database.

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© 2011 Springer-Verlag Berlin Heidelberg

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Brun, L., Conte, D., Foggia, P., Vento, M. (2011). People Re-identification by Graph Kernels Methods. In: Jiang, X., Ferrer, M., Torsello, A. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2011. Lecture Notes in Computer Science, vol 6658. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20844-7_29

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  • DOI: https://doi.org/10.1007/978-3-642-20844-7_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20843-0

  • Online ISBN: 978-3-642-20844-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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