基于鉴别性低秩表示的2阶段人脸识别算法

A Two-phase Face Recognition Algorithm Based on Discriminative Low-rank Representation

针对图像训练样本中存在噪声等情况,提出一种基于鉴别性低秩表示的2阶段人脸识别算法。该算法第1阶段是对所有训练样本进行低秩处理,筛选出M类与测试样本最相近的样本用于粗分类;第2阶段使用第1阶段筛选出来的样本做鉴别性低秩表示处理,并使用稀疏线性表示进行精细分类,决定测试样本最适合的类标签。本算法结合了低秩算法与稀疏算法的优点,在标准人脸库上的实验表明本算法表现优越。

A two-phase face recognition algorithm based on discriminative low-rank representation is proposed to deal with the noise in image training samples.In the first stage,all the training samples are processed by low-rank representation,and the M nearest neighbors of test sample are selected for rough classification.In the second stage,the samples screened in the first stage are used for discriminative low-rank representation,and sparse linear representation is used for fine classification,so as to determine the most suitable class labels for test samples.This algorithm combines the advantages of low-rank algorithm and sparse algorithm.The performance of this algorithm is proved by experiments on standard face database.