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Model-Based Varying Pose Face Detection and Facial Feature Registration in Video Images

机译:基于模型的不同姿势面部检测和视频图像中的面部特征注册

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This paper presents an automatic method for simultaneous human face detection and facial feature registration from colur video images. At the first stage, we sue a skin colour Gaussian model to dientify possible face locations under varying paose. Secondly, we compare image patterns with a varying pose face model in terms of shape and texture differences, using a combined feature-texture similarity measure (FTSM). False detections fro mthe first stage are eliminated by setting an appropriate FTSM threshold. Moreover, one can also register the facial features (eyes, nose and mouth) by aligning a prototype face with the unknown pose faces. Experimental results show that hte proposed method can achieve reliable face detection and feature registration under various consitions, including different poses, face appearances, and lighting conditions.
机译:本文介绍了来自Colur视频图像的同时人脸检测和面部特征注册的自动方法。在第一阶段,我们起诉皮肤彩色高斯模型,以将可能的面部位置拟定不同的佩索。其次,我们使用组合特征纹理相似度量(FTSM)在形状和纹理差异方面比较具有变化的姿势面部模型的图像模式。通过设置适当的FTSM阈值来消除FREES MTH MTH第一阶段。此外,人们还可以通过用未知的姿势面对准原型面部来注册面部特征(眼睛,鼻子和嘴)。实验结果表明,HTE所提出的方法可以在各种包装下实现可靠​​的面部检测和特征注册,包括不同的姿势,面部外观和照明条件。

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