厦门大学学报（自然科学版）2009，Vol.48Issue(4)：499-503,5.
基于选择性注意和部分连接神经网络的人脸识别
Face Recognition Based on Selective Attention and Parcone Model
摘要
Abstract
In order to overcome the loss of information and uncertainties in the previous methods of face recognition, this paper proposes a face recognition method in complex scene, and it does not need feature extraction. The method first used selective attention in the whole image, and then used Adaboost to search and locate the faces in the salience region. Finally, it put all pixels of the region which may contain face into trained partially connected neural evolutionary (Parcone) module to recognize. All of the recognition process was automatically and there is no need for image preprocessing. The experiments use MIT-CBCL face database and self-build image database, and the results show that this face recognition method has good recognition rate in complex background. The method in this paper can be applied to other types of target recognition.关键词
选择性注意/Parcone/Adaboost/人脸识别/特征提取Key words
selective attention/ Parcone/ Adaboost/ face recognition/ feature extraction分类
信息技术与安全科学引用本文复制引用
杨晔,Hugo de GARIS,潘伟,施明辉..基于选择性注意和部分连接神经网络的人脸识别[J].厦门大学学报（自然科学版）,2009,48(4):499-503,5.基金项目
福建省自然科学基金(2009J01305),厦门大学"985工程"二期项目资助 （2009J01305）
