The Study of Multi-Expression Classification Algorithm Based on Adaboost and Mutual Independent Feature
Liying Lang, Zuntao Hu
DOI: 10.4236/jsip.2011.24038   PDF   HTML     4,188 Downloads   6,627 Views   Citations


In the paper conventional Adaboost algorithm is improved and local features of face such as eyes and mouth are separated as mutual independent elements for facial feature extraction and classification. The multi-expression classification algorithm which is based on Adaboost and mutual independent feature is proposed. In order to effectively and quickly train threshold values of weak classifiers of features, Sample of training is carried out simple improvement. We obtain a good classification results through experiments.

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L. Lang and Z. Hu, "The Study of Multi-Expression Classification Algorithm Based on Adaboost and Mutual Independent Feature," Journal of Signal and Information Processing, Vol. 2 No. 4, 2011, pp. 270-273. doi: 10.4236/jsip.2011.24038.

Conflicts of Interest

The authors declare no conflicts of interest.


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