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Model-based varying pose face detection and facial feature registration in video images

机译:视频图像中基于模型的变化姿势面部检测和面部特征配准

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This paper presents an automatic method for simultaneous human face detection and facial feature registration from colour video images. At the first stage, we use a skin colour Gaussian model to identify possible face locations under varying pose. 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 from the 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 the proposed method can achieve reliable face detection and feature registration under various conditions, including different poses, face appearances, and lighting conditions.

机译:

本文提出了一种自动方法,用于同时从彩色视频图像进行人脸检测和面部特征配准。在第一阶段,我们使用肤色高斯模型来识别不同姿势下可能的脸部位置。其次,我们使用组合的特征-纹理相似性度量(FTSM)在形状和纹理差异方面比较具有变化的摆脸模型的图像模式。通过设置适当的FTSM阈值,可以消除来自第一阶段的错误检测。此外,还可以通过将原型面孔与未知的姿势面孔对齐来记录面部特征(眼睛,鼻子和嘴巴)。实验结果表明,该方法能够在不同的姿势,面部外观和光照条件下,实现可靠的人脸检测和特征配准。

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