CAJ | 학술논문

图像相似性先验嵌入的方法能有效提升基于稀疏编码表示的人脸识别在低维特征空间的识别性能。针对非受控人脸图像存在表情变化、部分遮挡和伪装的问题，提出基于图像分块的最大相似性嵌入稀疏编码表示的人脸识别方法。该方法首先将训练图像和测试图像进行同样的非重叠分块；然后计算测试图像与各训练图像对应分块间的相似性，并以其最大值度量图像间的相似性；最后将提取的最大块相似性信息嵌入到稀疏编码表示的人脸识别中。在AR标准人脸库上的测试表明，与全局相似性嵌入的加权稀疏编码表示分类方法相比，文中方法在训练样本和测试样本同时存在表情变化、遮挡和伪装的人脸识别中具有较大的性能提升。
도상상사성선험감입적방법능유효제승기우희소편마표시적인검식별재저유특정공간적식별성능。침대비수공인검도상존재표정변화、부분차당화위장적문제，제출기우도상분괴적최대상사성감입희소편마표시적인검식별방법。해방법수선장훈련도상화측시도상진행동양적비중첩분괴；연후계산측시도상여각훈련도상대응분괴간적상사성，병이기최대치도량도상간적상사성；최후장제취적최대괴상사성신식감입도희소편마표시적인검식별중。재AR표준인검고상적측시표명，여전국상사성감입적가권희소편마표시분류방법상비，문중방법재훈련양본화측시양본동시존재표정변화、차당화위장적인검식별중구유교대적성능제승。
The performance of sparse representation based face recognition ( SRFC) can be effectively improved by embedding a priori of similarity information. Aiming at expressions variations, partial occlusions and disguise in the uncontrolled face images, SRFC by embedding maximum block similarity information is proposed. Firstly, the training samples and query samples are divided into multiple non-overlapping blocks in the same way. Secondly, the similarities of corresponding blocks between the query samples and the training samples are calculated. Then, the maximum value is extracted to measure the similarity of inter-images. Finally, the extracted maximum block similarity information is embedded into sparse representation stage. Experimental results on AR face databases show that the proposed method achieves better recognition performance compared with those based on embedding global similarity, especially when both training images and query images contain expression, occlusions or disguise.