Abstract
In order to realize robust visual tracking in natural environments, a novel algorithm based on adaptive appearance model is proposed. The model can adapt to changes in object appearance over time. A mixture of three Gaussian distributions models the value of each pixel. An online Expectation Maximization (EM) algorithm is developed to update the parameters of the Gaussians. The observation model in the particle filter is designed based on the adaptive appearance model. Numerous experimental results demonstrate that our proposed algorithm can track objects well under illumination change, large pose variation, and partial or full occlusion.
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http://vision.stanford.edu/~birch , http://www.cs.toronto.edu/~dross/ivt
http://www.cs.toronto.edu/vis/projects/dudekfaceSequence.html
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© 2006 Springer-Verlag Berlin Heidelberg
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Hu, Sq., Liang, Gz., Jing, Zl. (2006). Robust Object Tracking Algorithm in Natural Environments. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881223_64
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DOI: https://doi.org/10.1007/11881223_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45907-1
Online ISBN: 978-3-540-45909-5
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