This paper is a study of the recognition of pose varied human faces images.
本文主要研究静止图像的多姿态人脸识别。
Such documents, containing multiple markup vocabularies, pose problems of recognition and collision.
这种包含多种标记词汇表的文档带来了识别和冲突问题。
Human face problems consist of four parts: human face detection, human face tracking, human face recognition and the derived analysis of pose and expression.
人脸问题主要包括：人脸检测、人脸跟踪、人脸识别，以及其衍生出来的姿态和表情分析四个应用领域。
Aiming at photo deception in face recognition system, a new face liveness verification algorithm using estimation of face pose variation is presented.
针对人脸识别系统中的欺骗手段，提出了一种基于姿态变化的脸部真实性判别算法。
The paper presents a method of pose-varied face recognition based on neural network and hierarchical support vector machines.
提出了一种基于神经网络和层次支持向量机的多姿态人脸识别方法。
This thesis mainly aiming at the method of algebraic character that is represented by SVD has done plenty of research work in the aspects of 3d object recognition and pose estimation.
本文主要针对以奇异值特征为代表的代数特征方法，在3d目标识别及姿态估计等方面做了大量研究工作。
The experiments on the ORL face database show that the recognition rate of the proposed method is high when pose, illumination condition, face expression and training sample number change.
在OR L人脸库的测试结果表明，在姿态、光照、表情、训练样本数目变化的情况下，该算法都具有较好的识别率。
The experiments on the ORL face database show that the recognition rate of the proposed method is high when pose, illumination condition, face expression and training sample number change.
在OR L人脸库的测试结果表明，在姿态、光照、表情、训练样本数目变化的情况下，该算法都具有较好的识别率。
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