| 基于概率支持向量机方法的人脸识别 |
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| 引用本文： | 肖小玲,李腊元.基于概率支持向量机方法的人脸识别[J].武汉理工大学学报(交通科学与工程版),2009,33(2). |
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| 作者姓名： | 肖小玲 李腊元 |
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| 作者单位： | 长江大学计算机学院,荆州,434023;武汉理工大学计算机科学与技术学院,武汉,430063 |
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| 基金项目： | 国家自然科学基金，教育部高等学校博士学科点专项科研基金，湖北省自然科学基金，中国石油科技创新基金 |
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| 摘 要： | 针对智能会议场景对人脸识别的特殊情况,通过依据检测、跟踪得到头部区域与人脸区域的面积比,选择正面的人脸进行识别,降低了人脸姿态对人脸识别的影响.在分类方法的选择上,采用支持向量机方法,并对支持向量机方法进行了概率建模,分类器输出结果是测试人脸属于每类的概率.实验结果表明:该方法不仅使人脸识别的精度得到了提高,还提供了其属于所在类中的可信程度.
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| 关 键 词： | 智能监控 概率 支持向量机 识别 |
Face Recognition Based on the Probability Outputs of Multi-class Support Vector Machines |
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| Xiao Xiaoling,Li Layuan.Face Recognition Based on the Probability Outputs of Multi-class Support Vector Machines[J].journal of wuhan university of technology(transportation science&engineering),2009,33(2). |
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| Authors: | Xiao Xiaoling Li Layuan |
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| Institution: | School of Computer Science;Yangtze University;Jingzhou 434023;School of Computer Science and Technology;Wuhan University of Technology;Wuhan 430063 |
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| Abstract: | To analyze face recognition in intelligent surveillance,face recognition based on the probability outputs of multi-class SVMs is proposed.Considering the special situation for face recognition in intelligent meeting scene,the front face is chosen for face recognition to reduce the pose effect,which is the ratio of the lengths or areas between the head and the face.The SVM method,which is modeled by the probability,is chosen as the classification method.The output of the SVM classifier is the probability of ... |
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| Keywords: | intelligent surveillance probability support vector machines recognition |
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