文章基本信息

标题：Fast Object Tracking Employing Labelled Particle Filter for Thermal Infrared Imager
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作者：Junying Yang ; Zhenghao Li ; Jingman Xia 等
期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2015
卷号：2015
DOI：10.1155/2015/497639
出版社：Hindawi Publishing Corporation
摘要：More and more network cameras are now working over distributed networks, offering the capability of remote intelligent video surveillance. In this paper, we bring forward an original particle filter tracking algorithm named labelled particle filter which describes each image patch with a binary label. Based on the imaging theory of thermography, moving objects, such as pedestrians and automobiles, usually have higher intensities compared with the background in a gray-level pseudocolor mode. Thus an image patch can be classified into two categories according to its intensity distribution, and we can use a one-bit binary label, positive or negative, to describe the attribute of image patch. Therefore, the candidate target template is established only if the label of candidate target matches the label of reference target, and the computational complexity is reduced consequently. Experiments are conducted to show that the proposed algorithm can handle real-time object tracking with less time cost while maintaining high tracking accuracy.