本文提出了一种新的张量子空间的学习算法：张量局部判别投影。
In this paper, a novel tensor subspace learning algorithm, tensor locality discriminant projection, is proposed.
主要研究内容包括：(1)提出一种增量式张量子空间学习的目标跟踪算法。
The main contributions of this paper are listed as follows. (1) An incremental tensor subspace learning based object tracking is presented.
最后，利用张量子空间分析分离出人脸图像的姿态信息并对其进行建模，实现人脸姿态估计，进而实现多姿态人脸识别。
Finally, view information of face images is extracted and modeled by TSA for the purpose of view estimation, which is followed by the multi-view face recognition.
最后，利用张量子空间分析分离出人脸图像的姿态信息并对其进行建模，实现人脸姿态估计，进而实现多姿态人脸识别。
Finally, view information of face images is extracted and modeled by TSA for the purpose of view estimation, which is followed by the multi-view face recognition.
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