The Role of Featural and Configural Information in Face Classification A Simulation of the Expertise Hypothesis

Author

Yafei Sun ; Sebe, Nicu ; Gevers, Theo ; Mercera, M.

Author_Institution

Sichuan Univ., Chengdu

Volume

1

fYear

0

fDate

0-0 0

Firstpage

1166

Lastpage

1170

Abstract

Face recognition in adults is the product of a unique mechanism in the brain and it is based on years of experience. The goal of this paper is to analyze the role of configural and featural information for face classification and to compare the performance of Bayesian network classifiers with the human performance in three experiments: similarity matching, gender, and race classification. Our results show that despite the fact that the machine classification results are worse than the one of the humans, they are consistent with human classification results

Keywords

belief networks; face recognition; feature extraction; image classification; Bayesian network classifier; configural information analysis; expertise hypothesis; face recognition; featural information analysis; gender classification; human face classification; machine classification; race classification; similarity matching; unique brain mechanism; Bayesian methods; Brain modeling; Face recognition; Humans; Information analysis; Mouth; Nose; Performance analysis; Psychology; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2006. ICPR 2006. 18th International Conference on

Conference_Location

Hong Kong

ISSN

1051-4651

Print_ISBN

0-7695-2521-0

Type

conf

DOI

10.1109/ICPR.2006.1122

Filename

1699097