Abstract
Face detection is an important component of the intelligent video surveillance system. Based on the MeanShift algorithm, we have developed into the CamShift algorithm. Although the traditional Camshift algorithm can track the moving object well, it has to set the tracking object by manually. Meanwhile it fails to track the object easily while the object is occluded and interfered by the same color obstructions. In order to solve the problem, according to the CamShift algorithm features, in this article, I will combine Adaboost, CamShift and Kalman filtering algorithm, which can be relied on to realize face detection and tracking automatically and accurately.
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Chen, K., Liu, C., Xu, Y. (2014). Face Detection and Tracking Based on Adaboost CamShift and Kalman Filter Algorithm. In: Fei, M., Peng, C., Su, Z., Song, Y., Han, Q. (eds) Computational Intelligence, Networked Systems and Their Applications. ICSEE LSMS 2014 2014. Communications in Computer and Information Science, vol 462. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45261-5_16
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DOI: https://doi.org/10.1007/978-3-662-45261-5_16
Publisher Name: Springer, Berlin, Heidelberg
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