DocumentCode :
3549170
Title :
Vehicle fingerprinting for reacquisition & tracking in videos
Author :
Guo, Yanlin ; Hsu, Steve ; Shan, Ying ; Sawhney, Harpreet ; Kumar, Rakesh
Author_Institution :
Sarnoff Corp., Princeton, NJ, USA
Volume :
2
fYear :
2005
fDate :
20-25 June 2005
Firstpage :
761
Abstract :
Visual recognition of objects through multiple observations is an important component of object tracking. We address the problem of vehicle matching when multiple observations of a vehicle are separated in time such that frames of observations are not contiguous, thus prohibiting the use of standard frame-to-frame data association. We employ features extracted over a sequence during one time interval as a vehicle fingerprint that is used to compute the likelihood that two or more sequence observations are from the same or different vehicles. The challenges of change in pose, aspect and appearances across two disparate observations are handled by combining feature-based quasi-rigid alignment with flexible matching between two or more sequences. The current work uses the domain of vehicle tracking from aerial platforms where typically both the imaging platform and the vehicles are moving and the number of pixels on the object are limited to fairly low resolutions. Extensive evaluation with respect to ground truth is reported in the paper.
Keywords :
feature extraction; fingerprint identification; image matching; image sequences; object recognition; optical tracking; vehicles; video signal processing; feature extraction; feature-based quasirigid alignment; frame-to-frame data association; multiple observations; object tracking; vehicle fingerprinting; vehicle matching problem; vehicle tracking; video reacquisition; video tracking; visual object recognition; Data mining; Feature extraction; Fingerprint recognition; Image resolution; Object recognition; Pixel; Tracking; Training data; Vehicles; Videos;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on
ISSN :
1063-6919
Print_ISBN :
0-7695-2372-2
Type :
conf
DOI :
10.1109/CVPR.2005.364
Filename :
1467519
Link To Document :
بازگشت