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(Reference retrieved automatically from SciELO through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A novel polar-based human face recognition computational model

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Author(s):
Y. Zana [1] ; J.P. Mena-Chalco [2] ; R.M. Cesar Jr. [3]
Total Authors: 3
Affiliation:
[1] Universidade Federal do ABC. Centro de Matemática, Computação e Cognição. Núcleo de Cognição e Sistemas Complexos - Brasil
[2] Universidade de São Paulo. Instituto de Matemática e Estatística. Departamento de Ciências da Computação - Brasil
[3] Universidade de São Paulo. Instituto de Matemática e Estatística. Departamento de Ciências da Computação - Brasil
Total Affiliations: 3
Document type: Journal article
Source: Brazilian Journal of Medical and Biological Research; v. 42, n. 7, p. 637-646, 2009-07-00.
Abstract

Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing. (AU)

FAPESP's process: 05/00587-5 - Mesh (graph) modeling and techniques of pattern recognition: structure, dynamics and applications
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants