Relational divergence based classification on Riemannian manifolds

A recent trend in computer vision is to represent images through covariance matrices, which can be treated as points on a special class of Riemannian manifolds. A popular way of analysing such manifolds is to embed them in Euclidean spaces, a process which can be interpreted as warping the feature s...

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Veröffentlicht in:	2013 IEEE Workshop on Applications of Computer Vision (WACV) S. 111 - 116
Hauptverfasser:	Alavi, A., Harandi, M. T., Sanderson, C.
Format:	Tagungsbericht Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.01.2013
Schlagworte:	Classification Computer vision Covariance matrix Divergence Encoding Euclidean geometry Face recognition Manifolds Measurement Surface layer Texture Training Vectors Workshops
ISBN:	9781467350532, 1467350532
ISSN:	1550-5790, 1550-5790
Online-Zugang:	Volltext
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