标题:Particle filter-based object tracking and handover in disjoint view multi-cameras
作者:Sun, Xiaoyan ;Chang, Faliang ;Dong, Wenhui
作者机构:[Sun, Xiaoyan ;Chang, Faliang ;Dong, Wenhui ] School of Control Science and Engineering, Shandong University, Shandong, China;[Sun, Xiaoyan ] School o 更多
通讯作者:Chang, F
来源:Advances in Intelligent Systems and Computing
出版年:2014
卷:215
页码:57-68
DOI:10.1007/978-3-642-37835-5_6
关键词:Camera handover; Multi-camera surveillance; Particle filter; Spatial-temporal information
摘要:In intelligent video surveillance, multiple cameras, even a distributed network of video sensors, have to be employed to monitor activities over a complex area nowadays. Hence, the continuous object tracking across multiple cameras and object handover between adjacent cameras is urgently needed, in which many appearance cues and spatial-temporal information can be employed. This paper fuses the spatial-temporal cues with appearance cues into a particle filter to handle the camera handover with multiple cameras having non-overlapping view. The spatial-temporal cues, including source and sink regions, their transition probabilities, and transition time among adjacent regions, are learned offline. Then a spatial-temporal progressive matching scheme using particle filter is proposed to deal with camera handover among adjacent cameras. In particle filter matching course, the commonly used appearance cue, i.e. the histogram in HSV color space is used. Once an object enters into sink region, we first continuously scatter particles in source regions related to this sink region according spatial-temporal information until the object emergence detected, and secondly, based on the particle weights of every source region, adjust their particle numbers till the camera handover is successfully completed. Encouraging experiment results show the efficiency of this scheme. © Springer-Verlag Berlin Heidelberg 2014.
收录类别:EI;SCOPUS
Scopus被引频次:1
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885055889&doi=10.1007%2f978-3-642-37835-5_6&partnerID=40&md5=213e340c43aa40dfcdd3271b42f5f1fb
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