Abstract
We present in this article a human detection and tracking algorithm using infrared vision in order to have reliable information on a room occupation. We intend to use this information to limit energetic consumption (light, heating). We perform first, a foreground segmentation with a Gaussian background model. A tracking step based on connected components intersections allows to collect information on 2D displacements of moving objects in the image plane. A classification based on a cascade of boosted classifiers is used for the recognition. Experimental results show the efficiency of the proposed algorithm.
This work was realized with the financial help of the Regional Council of Le Centre and the French Industry Ministry within the Capthom project of the Competitiveness Pole S2E2.
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Benezeth, Y., Emile, B., Laurent, H., Rosenberger, C. (2008). A Real Time Human Detection System Based on Far Infrared Vision. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds) Image and Signal Processing. ICISP 2008. Lecture Notes in Computer Science, vol 5099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69905-7_9
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DOI: https://doi.org/10.1007/978-3-540-69905-7_9
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