Title :
Person re-identification across multi-camera system based on local descriptors
Author :
Qiao Huang ; Jie Yang ; Yu Qiao
Author_Institution :
Key Lab. of Syst. Control & Inf. Process., Shanghai Jiao Tong Univ., Shanghai, China
fDate :
Oct. 30 2012-Nov. 2 2012
Abstract :
Tracking the same person across multiple cameras is an important task in multi-camera systems. It is also desirable to re-identify the individuals who have been previously seen with a single-camera. This paper addresses this problem by the re-identification of the same individual in two different datasets, which are both challenging situations from video surveillance system. In this paper, local descriptors are introduced for image description, and support vector machines are employed for high classification performance and so an efficient Bag of Features approach for image presentation. In this way, robustness against low resolution, occlusion and pose, viewpoint and illumination changes is achieved in a very fast way. We get promising results from the evaluation with situations where a number of individuals vary continuously from a multi-camera system.
Keywords :
cameras; hidden feature removal; image representation; image resolution; support vector machines; video surveillance; vocabulary; bag of features approach; dataset; high classification performance; image description; image occlusion; image posing; image presentation; image resolution; local descriptor; multicamera system; person reidentification; person tracking; support vector machine; video surveillance system; Cameras; Feature extraction; Histograms; Image color analysis; Kernel; Support vector machine classification; Vocabulary; bag of features; local descriptors; multicamera tracking; person re-identification; support vector machine;
Conference_Titel :
Distributed Smart Cameras (ICDSC), 2012 Sixth International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4503-1772-6