Tensor is a kind of data structure,which is basically multi-way array.Many data can be represented by tensor,such as face image.Feature extraction process is the most important part of face recognition while subsequent matching and identification process is based on it.TTr1SVD is a novel kind of tensor decomposition algorithm that can be thought as the extension of the matrix SVD towards tensor realm.The specific mode of the image in the image database is usually larger than the other modes,it is combined with TTr1SVD algorithm can further get the HOSVD to accelerate the facial feature extraction procedure.The organizations of the pictures were changed in the databases,which could be organized into different forms of tensor.TTr1SVD based tensor decomposition algorithm could extract facial features more efficiently and maintain good accuracy.Experimental results show that the proposed algorithm is more flexible and efficient than conventional tensor decomposition algorithms using Tensor Toolbox.%张量是一种数据组织形式,它的实质是高维数组.很多数据都可以被组织成张量的形式,可以考虑将人脸图像组织成张量的形式.人脸识别过程中最重要的一个环节是特征提取,后续的匹配识别过程是建立在它的基础上.TTr1SVD是一种新型的张量分解算法,可以认为该算法是矩阵SVD在张量领域的扩展.实际数据库中图片的图像模态往往是最大的,结合TTr1SVD算法,得到张量的高阶奇异值分解,改变图片的组织形式,可以加速人脸特征的提取.基于TTr1SVD的高阶奇异值分解算法,实现人脸特征的提取和识别,并且保持了较好的准确性.实验结果表明,该算法比传统的使用Tensor Toolbox的高阶奇异值分解算法更加灵活高效.
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