Abstract
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.
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Acknowledgments
We would like to acknowledge the support from China Natural Science Foundation Committee (No. 60975025, No. 61273277), the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry (20101174), Shandong province Natural Science Foundation Committee (No. ZR2011FM032), and the University Innovation Program from Jinan Science and Technology Bureau (No. 201004002).
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Sun, X., Chang, F., Dong, W. (2014). Particle Filter-Based Object Tracking and Handover in Disjoint View Multi-Cameras. In: Sun, F., Hu, D., Liu, H. (eds) Foundations and Practical Applications of Cognitive Systems and Information Processing. Advances in Intelligent Systems and Computing, vol 215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37835-5_6
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DOI: https://doi.org/10.1007/978-3-642-37835-5_6
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