Modelfest: principal component analysis reveals underlying channel structure
Chien‐Chung Chen, Christopher W. Tyler · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2000
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.