关键词: Boosting思想, 复用特征, 人脸识别

Abstract: Face recognition for one training sample is one of the most challenge tasks. Many developed systems, that work very well when there are sufficient representative training samples, often become less effective or low accuracy for one training sample. After analysing the local facial features, several significant features to represent the human face were selected. Then a novel algorithm of feature extraction for single sample by exploiting repeatedly the selected face features was proposed following the Boosting methods. Finally, two face recognition systems were built by combining whole face features with local face features—— voting-based method with multi-features and mothod with repeatedly used features. The experiments show that the developed systems have good performance in comparison with the existing system.

Key words: Boosting methods, repeatedly used features, face recognition