2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops (2005)

San Diego, California

June 20, 2005 to June 26, 2005

ISSN: 1063-6919

ISBN: 0-7695-2660-8

pp: 42

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2005.445

Herve Abdi , The University of Texas at Dallas

Alice J. O?Toole , The University of Texas at Dallas

Dominique Valentin , Universite de Bourgogne

Betty Edelman , The University of Texas at Dallas

ABSTRACT

<p>In this paper we present a generalization of classical multidimensional scaling called DISTATIS which is a new method that can be used to compare algorithms when their outputs consist of distance matrices computed on the same set of objects. The method first evaluates the similarity between algorithms using a coefficient called the RV coefficient. From this analysis, a compromise matrix is computed which represents the best aggregate of the original matrices. In order to evaluate the differences between algorithms, the original distance matrices are then projected onto the compromise. We illustrate this method with a "toy example" in which four different "algorithms" (two computer programs and two sets of human observers) evaluate the similarity among faces.</p>

INDEX TERMS

null

CITATION

D. Valentin, A. J. O?Toole, H. Abdi and B. Edelman, "DISTATIS: The Analysis of Multiple Distance Matrices,"

*2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops(CVPRW)*, San Diego, California, 2005, pp. 42.

doi:10.1109/CVPR.2005.445

CITATIONS

SEARCH