IPSJ Transactions on Computer Vision and Applications
Online ISSN : 1882-6695
ISSN-L : 1882-6695
A Discriminative Metric Learning Algorithm for Face Recognition
Tsuyoshi KatoWataru TakeiShinichiro Omachi
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2013 Volume 5 Pages 85-89


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.

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© 2013 by the Information Processing Society of Japan
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