Abstract
In this paper, a new method for shadow detection is proposed. The proposed method models shadows by the Gaussian mixture model with the Dirichlet process mixture model. The parameters of the shadow model with the Dirichlet process mixture model are estimated by the Dirichlet Process EM algorithm. The proper number of the distribution can be determined through the process estimating the parameters without calculating the probability densities with two or more different number of distributions. Shadows are detected by the probability density calculated with the shadow model. The method for improving the accuracy of the result is also proposed.
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Kurahashi, W., Fukui, S., Iwahori, Y., Woodham, R.J. (2010). Shadow Detection Method Based on Dirichlet Process Mixture Model. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15393-8_11
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DOI: https://doi.org/10.1007/978-3-642-15393-8_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15392-1
Online ISBN: 978-3-642-15393-8
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