We establish a facial feature location and templatematching based face detection system on PC and experiments are carried.
在PC机上,建立了基于特征提取和模板匹配的人脸检测系统,并进行了大量试验。
参考来源 - 基于特征与模板的人脸检测算法的研究和应用·2,447,543篇论文数据，部分数据来源于NoteExpress
Active Appearance Models (AAMs) is an effective method of facial recognition and facial feature location, and has become a research hotspot in image processing areas.
主动外观模型是进行人脸面部特征定位和人脸识别的有效方法，近年来已成为图像处理等领域的研究热点。
Parameter ranges of the deformable templates are limited in the rectangle of feature location, and energy function minimum corresponds to the best position of facial feature.
在特征定位的矩形框内限定变形模板的参数范围，当能量函数达到最小值时对应变形模板匹配的最佳位置。
After upper facial action unit location and segmentation, we present the facial action unit feature extraction algorithm based on KPCA.
在定位分割出上半人脸运动单元子区域图像之后，提出了采用KPCA算法提取它们的特征。
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