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一种基于Real AdaBoost算法的EOM人脸检测方法 被引量：1

EOM Face Detection Method Based on Real AdaBoost Algorithm
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摘要 提出一种基于Real AdaBoost算法的边缘方位匹配(EOM)人脸检测方法。该方法提取人脸图像的边缘方位特征,一定程度上克服光照等干扰因素的影响。采用Real AdaBoost算法通过多次迭代学习过程获取人脸的整体模式(全局特征点集)。在每次迭代学习过程中,采用区域选择策略获取人脸的局部模式(局部特征点集),与传统的EOM方法相比,本文方法所获取的人脸模式更精确,正面人脸检测实验证实这一点。 A Real AdaBoost algorithm based EOM （edge-orientation matching） method is proposed for face detection. The edge orientation feature is extracted from the original face images to eliminate the influence of some disturbances such as variable lighting to a certain extent. The global face pattern （global feature point set） is obtained by using the Real AdaBoost algorithm through multiple iterative learning procedures, and the local pattern （local feature point set） is acquired by utilizing the area-selecting strategy during each iterative procedure. A precise face pattern is found by the proposed method rather than by the original EOM method, which is confirmed by the experiment of frontal face detection.
作者 陈华杰 韦巍
机构地区 浙江大学电气工程学院
出处 《模式识别与人工智能》 EI CSCD 北大核心 2006年第6期812-817,共6页 Pattern Recognition and Artificial Intelligence
关键词 人脸检测 边缘方位匹配(EOM)方法 REAL ADABOOST算法 区域选择策略 Face Detection, Edge-Orientation Matching （EOM） Method, Real AdaBoost Algorithm,Area-Selecting Strategy
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献17

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模式识别与人工智能
2006年 第6期

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