Abstract
In this paper, we propose an Active Appearance Models (AAMs) fitting algorithm, adaptive fitting algorithm, to localize an object in an image containing occlusion. The adaptive fitting algorithm conducts the fitting problem of AAMs containing object occlusion in a statistical framework. We assume that the residual errors can be treated as mixture statistical model of Gaussian and uniform model. We then reformulated the basic fitting algorithm and maximum a-posteriori (MAP) estimation algorithm of model parameter for AAMs to make the adaptive fitting algorithm. Extensive experiments are provided to demonstrate our algorithm.
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Yu, X., Tian, J., Liu, J. (2007). Active Appearance Models Fitting with Occlusion. In: Yuille, A.L., Zhu, SC., Cremers, D., Wang, Y. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2007. Lecture Notes in Computer Science, vol 4679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74198-5_11
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DOI: https://doi.org/10.1007/978-3-540-74198-5_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74195-4
Online ISBN: 978-3-540-74198-5
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