Inferring image templates from classification decisions

Authors:
Arnab Dhua;Florin Cutzu
Affiliations:
Computer Science Department, Indiana University, Bloomington, IN;Computer Science Department, Indiana University, Bloomington, IN
Venue:
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Year:
2005

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Abstract

Assuming human image classification decisions are based on estimating the degree of match between a small number of stored internal templates and certain regions of the input images, we present an algorithm which infers observers classification templates from their classification decisions on a set of test images. The problem is formulated as learning prototypes from labeled data under an adjustable, prototype-specific elliptical metric. The matrix of the elliptical metric indicates the pixels that the template responds to. The model was applied to human psychophysical data collected in a simple image classification experiment.