15 November 2007 Framework for feature selection for cast shadow removal
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Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678606 (2007) https://doi.org/10.1117/12.748631
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
Cast shadow cause serious problem in the extracting of moving objects because shadow pixels are liable to be misclassified as foreground. Many methods of cast shadow removal have been proposed and many features are selected in these methods. But since, moving object (MO) and cast shadow are classified by a single linear classifier. As it is known, each feature has its strength and weakness and is particularly applicable for handling a certain type of variation. In this paper, a novel framework for feature selection for cast shadow removal based on AdaBoost is proposed. Experiments are conducted on many scenes and the results prove the validation of the proposed method.
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Guilin Zhang, Guilin Zhang, Ying Chu, Ying Chu, Song Tian, Song Tian, Yufei Zha, Yufei Zha, Gengming Zhu, Gengming Zhu, } "Framework for feature selection for cast shadow removal", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678606 (15 November 2007); doi: 10.1117/12.748631; https://doi.org/10.1117/12.748631
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