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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Vydané v:	2012 IEEE Conference on Computer Vision and Pattern Recognition s. 2288 - 2295
Hlavní autori:	Kostinger, M., Hirzer, M., Wohlhart, P., Roth, P. M., Bischof, H.
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.06.2012
Predmet:	Benchmark testing Measurement Optimization Scalability Support vector machines Training
ISBN:	9781467312264, 1467312266
ISSN:	1063-6919, 1063-6919
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