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Video Sequences Association for People Re-identification across Multiple Non-overlapping Cameras

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Part of the book series:Lecture Notes in Computer Science ((LNIP,volume 5716))

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Abstract

This paper presents a solution of the appearance-based people re-identification problem in a surveillance system including multiple cameras with different fields of vision. We first utilize different color-based features, combined with several illuminant invariant normalizations in order to characterize the silhouettes in static frames. A graph-based approach which is capable of learning the global structure of the manifold and preserving the properties of the original data in a lower dimensional representation is then introduced to reduce the effective working space and to realize the comparison of the video sequences. The global system was tested on a real data set collected by two cameras installed on board a train. The experimental results show that the combination of color-based features, invariant normalization procedures and the graph-based approach leads to very satisfactory results.

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Author information

Authors and Affiliations

  1. French National Institute for Transport and Safety Research (INRETS), 20 rue Elise Reclus, 59650, Villeneuve d’Ascq, France

    Dung Nghi Truong Cong, Louahdi Khoudour & Lounis Douadi

  2. Institute of Intelligent Systems and Robotics (ISIR), UPMC Univ Paris 06, Case Courrier 252, 3 rue Galile, 94200, IVRY SUR SEINE, France

    Catherine Achard

Authors
  1. Dung Nghi Truong Cong
  2. Catherine Achard
  3. Louahdi Khoudour
  4. Lounis Douadi

Editor information

Editors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione e Ingegneria Elettrica, Università di Salerno, Via Ponte Don Melillo, 1, 84084, Fisciano (SA), Italy

    Pasquale Foggia

  2. Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II, Via Claudio, 21, I-80125, Napoli, Italy

    Carlo Sansone

  3. Dipartimento di Ingegneria dell’Informazione ed Ingegneria Elettrica, Università di Salerno, via P.te Don Melillo, I-84084, Fisciano (SA), Italy

    Mario Vento

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© 2009 Springer-Verlag Berlin Heidelberg

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Truong Cong, D.N., Achard, C., Khoudour, L., Douadi, L. (2009). Video Sequences Association for People Re-identification across Multiple Non-overlapping Cameras. In: Foggia, P., Sansone, C., Vento, M. (eds) Image Analysis and Processing – ICIAP 2009. ICIAP 2009. Lecture Notes in Computer Science, vol 5716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04146-4_21

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