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Accurate Facial Feature Localization on Expressional Face Images Based on a Graphical Model Approach

机译:基于图形模型方法的表情面部图像精确人脸特征定位

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Recent emergent face-related applications, such as face recognition and facial expression recognition, usually rely on accurate facial feature point localization. However, the variations in facial appearance, especially due to expressions, often make accurate localization of facial features very difficult. This paper proposes a graphical-model based approach for facial feature localization on expressional face images. By using the model, for localization while the influence between its local appearance and relative position is balanced. The experimental results show that our algorithm gives more accurate results than ASM and the AdaBoost-based facial feature detectors on Cohn-Kanade face database.
机译:诸如面部识别和面部表情识别之类的最近涌现的与面部相关的应用通常依赖于准确的面部特征点定位。然而,面部外观的变化,特别是由于表情的变化,常常使面部特征的精确定位非常困难。本文提出了一种基于图形模型的方法来在表情人脸图像上进行人脸特征定位。通过使用该模型进行定位,同时平衡了其局部外观和相对位置之间的影响。实验结果表明,与Cohn-Kanade人脸数据库中的ASM和基于AdaBoost的人脸特征检测器相比,我们的算法给出的结果更为准确。

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