Skip to Main content Skip to Navigation
Conference papers

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.
Complete list of metadata

Cited literature [18 references]  Display  Hide  Download
Contributor : Donatello Conte Connect in order to contact the contributor
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


Files produced by the author(s)



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⟩



Record views


Files downloads