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Max-correlation embedding computation

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conference contribution
posted on 2014-01-01, 00:00 authored by Antonio Robles-KellyAntonio Robles-Kelly
In 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

Volume

8621

Pagination

113-122

Location

Joensuu, Finland

Start date

2014-08-20

End date

2014-08-22

ISBN-13

978-3-662-44414-6

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2014, Springer-Verlag Berlin Heidelberg

Editor/Contributor(s)

Fränti P, Brown G, Loog M, Escolano F, Pelillo M

Title 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) 2014

Event

International Association for Pattern Recognition. Workshops (2014 : Joensuu, Finland)

Publisher

Springer

Place of publication

Berlin, Germany

Series

International Association for Pattern Recognition Workshops

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