The Study of Multi-Expression Classification Algorithm Based on Adaboost and Mutual Independent Feature

Liying Lang, Zuntao Hu

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DOI: 10.4236/jsip.2011.24038                

Abstract

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.

Keywords

Adaboost Multi-Expression Classification Algorithm, Local Feature, Feature Extraction, Sample Training

Conflicts of Interest

The authors declare no conflicts of interest.

References

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