文章基本信息

标题：A Discriminative Metric Learning Algorithm for Face Recognition
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作者：Tsuyoshi Kato ; Wataru Takei ; Shinichiro Omachi 等
期刊名称：Information and Media Technologies
电子版ISSN：1881-0896
出版年度：2013
卷号：8
期号：4
页码：1076-1080
DOI：10.11185/imt.8.1076
出版社：Information and Media Technologies Editorial Board
摘要：Face recognition is a multi-class classification problem that has long attracted many researchers in the community of image analysis. We consider using the Mahalanobis distance for the task. Classically, the inverse of a covariance matrix has been chosen as the Mahalanobis matrix, a parameter of the Mahalanobis distance. Modern studies often employ machine learning algorithms called metric learning to determine the Mahalanobis matrix so that the distance is more discriminative, although they resort to eigen-decomposition requiring heavy computation. This paper presents a new metric learning algorithm that finds discriminative Mahalanobis matrices efficiently without eigen-decomposition, and shows promising experimental results on real-world face-image datasets.
关键词：face recognition;metric learning;Mahalanobis distance;optimization;nearest neighbor classifier