Large scale metric learning from equivalence constraints

In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization procedures are applied that become computationally intractable on a large scale. Further, if one considers the constantly...

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Bibliographic Details

Published in:	2012 IEEE Conference on Computer Vision and Pattern Recognition pp. 2288 - 2295
Main Authors:	Kostinger, M., Hirzer, M., Wohlhart, P., Roth, P. M., Bischof, H.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.06.2012
Subjects:	Benchmark testing Measurement Optimization Scalability Support vector machines Training
ISBN:	9781467312264, 1467312266
ISSN:	1063-6919, 1063-6919
Online Access:	Get full text
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