A graph-kernel method for re-identification
Résumé
Re-identification, that is recognizing that an object appear- ing in a scene is a reoccurrence of an object seen previously by the sys- tem (by the same camera or possibly by a different one) is a challenging problem in video surveillance. In this paper, the problem is addressed using a structural, graph-based representation of the objects of inter- est. A recently proposed graph kernel is adopted for extending to this representation the Principal Component Analyisis (PCA) technique. An experimental evaluation of the method has been performed on two video sequences from the publicly available PETS2009 database.
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