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. © 2011 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Brun, L., Conte, D., Foggia, P., & Vento, M. (2011). People Re-identification by graph kernels methods. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6658 LNCS, 285–294. https://doi.org/10.1007/978-3-642-20844-7_29
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