Title
People re-identification by classification of silhouettes based on sparse representation
Abstract
The research presented in this paper consists in developing an automatic system for people re-identification across multiple cameras with non-overlapping fields of view. We first propose a robust algorithm for silhouette extraction which is based on an adaptive spatio-colorimetric background and foreground model coupled with a dynamic decision framework. Such a method is able to deal with the difficult conditions of outdoor environments where lighting is not stable and distracting motions are very numerous. A robust classification procedure, which exploits the discriminative nature of sparse representation, is then presented to perform people re-identification task. The global system is tested on two real data sets recorded in very difficult environments. The experimental results show that the proposed system leads to very satisfactory results compared to other approaches of the literature.
Year
DOI
Venue
2010
10.1109/IPTA.2010.5586809
IPTA
Keywords
Field
DocType
sparse representation,motions distraction,silhouette extraction,people reidentification,sparse matrices,camera,spatiocolorimetric foreground,spatiocolorimetric background,silhouette classification,robust algorithm,feature extraction,cameras,discriminative nature,dynamic decision framework,people detection,robust classification procedure,people re-identification,surveillance system,video surveillance,data set,robustness,field of view,pixel
Computer vision,Data set,Pattern recognition,Computer science,Silhouette,Sparse approximation,Robustness (computer science),Feature extraction,Pixel,Artificial intelligence,Discriminative model,Sparse matrix
Conference
ISSN
ISBN
Citations 
2154-5111
978-1-4244-7247-5
9
PageRank 
References 
Authors
0.53
9
3
Name
Order
Citations
PageRank
Dung Nghi Truong Cong1534.14
Catherine Achard215819.60
Louahdi Khoudour311714.20