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首页> 外文会议>2012 international conference on future communication and computer technology >Face Recognition Based on AAM Attitude Alignment
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Face Recognition Based on AAM Attitude Alignment

机译：基于AAM姿态对准的人脸识别

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摘要

In the unconstrained environment, face recognition results can be seriously affected by the inner and outer factors such as expression, attitude, light conditions and background. Active Appearance Model (AAM) can build the priori model with shape and texture information to synthesize new face images. In this paper, the shape model of AAM, which can expresses the variation of face attitude, is removed so that the face images are aligned to new synthesized images without the attitude influence. By improving AAM, we reduce some inner and outer effects on recognition process, and the attitude changes especially can be removed. Face recognitions based on Standard Model Features (SMFs) with SVM is carried on IMM database. Experiment results indicate that the recognition for face images aligned by AAM gets a better recognition rate.
机译：在不受限制的环境中，人脸识别结果会受到表情，姿势，光线条件和背景等内在和外在因素的严重影响。主动外观模型（AAM）可以使用形状和纹理信息构建先验模型，以合成新的面部图像。本文去除了可以表达人脸姿态变化的AAM形状模型，使人脸图像与新合成的图像对齐，而不受姿态影响。通过改进AAM，我们减少了识别过程中的一些内在和外在影响，尤其是可以消除态度变化。基于标准模型特征（SMF）和SVM的人脸识别在IMM数据库中进行。实验结果表明，通过AAM对齐的人脸图像识别率更高。

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