Abstract
This paper focuses on people tracking within a building with the installment of distributed overhead cameras. Our primary concern is to keep tracks of: number of people entrance to a particular area; and the whereabouts trajectory of a particular person within the monitored building. With image taken from ceiling mounted camera, pedestrian’s physiologic contour is analyzed from four different viewing angles to form a person’s identity signature. In doing so, techniques to locate a person’s head, to predict his/her movement direction, to separate overlapped physiological blobs, and to differentiate different people by color histogram classifier have been proposed. Special attention has been paid for system configurability such that the proposed software architecture can be deployed to different floor plans. We have conducted a continuing surveillance monitoring on the third floor of EE in NTUST, and the result shows moderate surveillance performance: 93% accuracy in entrance counting, and 76% accuracy in identification checking.
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Lin, CH., Chung, SL., Guo, JM. (2011). People Tracking in a Building Using Color Histogram Classifiers and Gaussian Weighted Individual Separation Approaches. In: Lee, KT., Tsai, WH., Liao, HY.M., Chen, T., Hsieh, JW., Tseng, CC. (eds) Advances in Multimedia Modeling. MMM 2011. Lecture Notes in Computer Science, vol 6524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17829-0_17
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DOI: https://doi.org/10.1007/978-3-642-17829-0_17
Publisher Name: Springer, Berlin, Heidelberg
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