Human tracking by ip ptz camera control in the context of video surveillance

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Abstract

In this paper, a fuzzy feature-based method for online people tracking using an IP PTZ camera is proposed. It involves five steps: 1) target modeling, 2) track initialization, 3) blob extraction, 4) target localization using a fuzzy classifier, and 5) IP PTZ camera control. It selects the most similar target among candidate blobs found in the image using skin and motion detection. Results show that the proposed method has a good target detection precision (>∈89%), low track fragmentation, and the target is almost always localized within 1/6th of the image diagonal from the image center. In addition, results suggest that our tracking method can cope with occlusion and large motion of the target. © 2009 Springer Berlin Heidelberg.

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Varcheie, P. D. Z., & Bilodeau, G. A. (2009). Human tracking by ip ptz camera control in the context of video surveillance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5627 LNCS, pp. 657–667). https://doi.org/10.1007/978-3-642-02611-9_65

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