基于支持向量机的人脸识别方法

1.引言人脸是人类视觉中的常见模式,人脸识别在安全验证系统、公安(犯罪识别等)、医学、视频会议、交通量控制等方面有着广阔的应用前景。现有的基于生物特征的识别技术,包括语音识别、虹膜识别、指纹识别等,都已用于商业应用。然而最吸引人的还是人脸识别,因为从人机交互的方式来看,人脸识别更符合人们的理想。虽然人能毫不费力地识别出人脸及其表情,但人脸的机器自动识别仍然是一个具挑战性的研究领域。由于人脸结构的复杂性以及人脸表情的多样性、成像过

Face Recognition Using Support Vector Machines

Support Vector Machines are a binary classification method and have demonstrated excellent results in pattern recognition. Face recognition is a multi-class problem, where the number of classes is of the known individuals. In this paper we use face data extracted from Eigenfeatures and develope a method to extend SVM to using in multi-class. The training set consists of 5 images of each of the 50 persons equally distributed among frontal, approximately 15°rotated respectively, and the test set consists of 10 images each of the 50 persons. In the ICT-YC face gallery, the proposed system obtains competitive results highly: a correct recognition rate of 94.8％ for all the 50 persons, to the less number of the persons and to the famous ORL face gallery we also get good face recognition rate.