2008年 第10卷 第7期
基于沃尔什特征的增强型AdaBoost 人脸快速检测算法
1. 南京理工大学计算机科学与技术学院，南京210094；
2. 扬州大学信息工程学院，江苏扬州225009
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摘要
提出一种基于沃尔什特征的增强型AdaBoost 人脸快速检测算法，不仅具有很快的训练速度，而且利 用较少的非人脸样本进行训练就可以达到较好的检测效果。首先，提出用较少的沃尔什特征来代替大量的 Harr-Like 特征可以较大幅度的降低特征之间的冗余。然后提出一种双阈值增强型AdaBoost 算法，其中双阈 值的快速搜索方法大大节约了训练时间，并且在训练Cascaded 检测器过程中，前层分类器的训练结果对后层 分类器的训练具有指导作用，加强了总体检测器的性能，另外通过各层分类器阈值的调节，能够将人脸和非 人脸的训练结果尽量分离。最后，使用该算法训练的检测器对MIT＋CMU 人脸测试库进行了测试，结果表明 该方法在训练速度、测试精度、检测时间等方面都优于相应的方法。
关键词
沃尔什特征 ; 增强型AdaBoost ; Cascaded 型检测器 ; 人脸检测
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参考文献
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