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Max-correlation embedding computation
conference contribution
posted on 2014-01-01, 00:00 authored by Antonio Robles-KellyAntonio Robles-KellyIn this paper, we present a method to compute an embedding matrix which maximises the dependence of the embedding space upon the graph-vertex coordinates and the incidence mapping of the graph. This treatment leads to a convex cost function which, by construction, attains its maximum at the leading singular value of a matrix whose columns are given by the incidence mapping and the embedded vertex coordinates. This, in turn, maximises the correlation between the spaces in which the embedding and the graph vertex coordinates are defined. It also maximises the dependence between the embedding and the incidence mapping of the graph. We illustrate the utility of the method for purposes of approximating the colour sensitivity functions of a set of over 20 commercially available digital cameras using a library of spectral reflectance measurements.
History
Event
International Association for Pattern Recognition. Workshops (2014 : Joensuu, Finland)Volume
8621Series
International Association for Pattern Recognition WorkshopsPagination
113 - 122Publisher
SpringerLocation
Joensuu, FinlandPlace of publication
Berlin, GermanyPublisher DOI
Start date
2014-08-20End date
2014-08-22ISBN-13
978-3-662-44414-6Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2014, Springer-Verlag Berlin HeidelbergEditor/Contributor(s)
P Fränti, G Brown, M Loog, F Escolano, M PelilloTitle of proceedings
S+SSPR 2014 : Proceedings of the Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR) 2014Usage metrics
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