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Proceedings Paper

Modelfest: principal component analysis reveals underlying channel structure
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Paper Abstract

In Year One of the Modelfest project, several laboratories collaborated to collect threshold data of human observers on 45 pattern stimuli. In this preliminary study, we used a principal component analysis (PCA) and a confirmatory factor analysis on the variations among observers to explore the underlying visual mechanisms for detecting Modelfest Stimuli. This analysis is based on the assumption that there are channels in common among observers that are represented with variations in sensitivity level only. We found three principal components. Assuming that each principal component represents a single mechanism, we compute the sensitivity profile of each mechanism as the sum of test stimuli weighted by the factor loadings on each component. The first mechanism is a spot detector. The second mechanism is dominated by a horizontal periodic pattern around 4 c/deg and the third may be characterized as a narrow bar detector.

Paper Details

Date Published: 2 June 2000
PDF: 8 pages
Proc. SPIE 3959, Human Vision and Electronic Imaging V, (2 June 2000); doi: 10.1117/12.387151
Show Author Affiliations
Chien-Chung Chen, Smith-Kettlewell Eye Research Institute (Canada)
Christopher W. Tyler, Smith-Kettlewell Eye Research Institute (United States)

Published in SPIE Proceedings Vol. 3959:
Human Vision and Electronic Imaging V
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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