融合SIFT和MIL的红外人脸识别方法
李大湘;赵小强;刘颖;王殿伟
【期刊名称】《西安邮电学院学报》 【年(卷),期】2012(017)004
【摘要】For the problem of infrared image face recognition, a novel algorithm based on SIFT feature and multi-instance learning （MIL） algorithm is proposed. Firstly, this algorithm regards image as a bag, and SIFT descriptor of the key points as instance. Then all the SIFT descriptors in the training set have been clustered by K-Means method, and regards cluster centers as ＂visual word＂ to build ＂visual vocabulary table＂; Secondly, according to the frequency of ＂visual word＂ in the training bag to establish a ＂word-document＂ matrix, then latent semantic analysis （LSA） method is used to obtain bag＇ s （image） latent semantic features, converts MIL problem to a standard supervised learning problem, which means to solve MIL problem use SVM in the latent semantic space. Experimental results on the OTBCVS image set show that the algorithm proposed is feasible, and the performance is superior to other algorithms.%针对红外人脸识别问题,提出一种新的基于尺度不变特征转换（SIFT）与多示例学习（MIL）相结合的算法。该算法将图像当作多示例包,SIFT描述子当作包中的示例,利用聚类的方法对训练集中的所有SIFT描述子进行聚类,建立＂视觉词汇表＂,再根据＂视觉字＂在多示例训练包中出现的频率,建立＂词-文档＂矩阵,采用潜在语义分析（LSA）
融合SIFT和MIL的红外人脸识别方法
