DocumentCode :
2085938
Title :
Person Reidentification Using Spatiotemporal Appearance
Author :
Gheissari, N. ; Sebastian, T.B. ; Hartley, Richard
Author_Institution :
National ICT Canberra, Australia
Volume :
2
fYear :
2006
fDate :
2006
Firstpage :
1528
Lastpage :
1535
Abstract :
In many surveillance applications it is desirable to determine if a given individual has been previously observed over a network of cameras. This is the person reidentification problem. This paper focuses on reidentification algorithms that use the overall appearance of an individual as opposed to passive biometrics such as face and gait. Person reidentification approaches have two aspects: (i) establish correspondence between parts, and (ii) generate signatures that are invariant to variations in illumination, pose, and the dynamic appearance of clothing. A novel spatiotemporal segmentation algorithm is employed to generate salient edgels that are robust to changes in appearance of clothing. The invariant signatures are generated by combining normalized color and salient edgel histograms. Two approaches are proposed to generate correspondences: (i) a model based approach that fits an articulated model to each individual to establish a correspondence map, and (ii) an interest point operator approach that nominates a large number of potential correspondences which are evaluated using a region growing scheme. Finally, the approaches are evaluated on a 44 person database across 3 disparate views.
Keywords :
Biometrics; Brightness; Cameras; Clothing; Face detection; Histograms; Lighting; Robustness; Spatiotemporal phenomena; Surveillance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on
ISSN :
1063-6919
Print_ISBN :
0-7695-2597-0
Type :
conf
DOI :
10.1109/CVPR.2006.223
Filename :
1640938
Link To Document :
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