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Tracking System with Re-identification Using a RGB String Kernel

Abstract : People re-identification consists to identify a person which comes back in a scene where it has been previously detected. This key problem in visual surveillance applications may concern single or multi camera systems. Features encoding each person should be rich enough to provide an efficient re-identification while being sufficiently robust to remain significant through the different phenomena which may alter the appearance of a person in a video. We propose in this paper a method which encodes people's appearance through a string of salient points. The similarity between two such strings is encoded by a kernel. This last kernel is combined with a tracking algorithm in order to associate a set of strings to each person and to measure similarities between persons entering into the scene and persons who left it.
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https://hal.archives-ouvertes.fr/hal-01083074
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Submitted on : Saturday, November 15, 2014 - 10:18:05 AM
Last modification on : Saturday, June 25, 2022 - 9:49:27 AM
Long-term archiving on: : Monday, February 16, 2015 - 10:10:11 AM

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Amal Mahboubi, Luc Brun, Donatello Conte, Pasquale Foggia, Mario Vento. Tracking System with Re-identification Using a RGB String Kernel. Joint IAPR International Workshop, S+SSPR 2014, Aug 2014, Joensuu, Finland. pp.333 - 342, ⟨10.1007/978-3-662-44415-3_34⟩. ⟨hal-01083074⟩

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