Recognizing Disguised Faces: Human and Machine Evaluation

Face verification, though an easy task for humans, is a long-standing open research area. This is largely due to the challenging covariates, such as disguise and aging, which make it very hard to accurately verify the identity of a person. This paper investigates human and machine performance for re...

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Published inPloS one Vol. 9; no. 7; p. e99212
Main Authors Dhamecha, Tejas Indulal, Singh, Richa, Vatsa, Mayank, Kumar, Ajay
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 16.07.2014
Public Library of Science (PLoS)
Subjects
Access control
Age Factors
Aging
Algorithms
Automation
Biometric Identification - methods
Biometric Identification - trends
Biometrics
Computer science
Cybernetics
Discriminant analysis
Engineering and Technology
Face
Face recognition
Familiarity
Female
Human performance
Humans
International conferences
Male
Matching
Minority & ethnic groups
Pattern Recognition, Visual - physiology
Photic Stimulation
Principal components analysis
Recognition (Psychology) - physiology
Surveillance
Surveys and Questionnaires
Hong Kong China
China
India
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Summary:Face verification, though an easy task for humans, is a long-standing open research area. This is largely due to the challenging covariates, such as disguise and aging, which make it very hard to accurately verify the identity of a person. This paper investigates human and machine performance for recognizing/verifying disguised faces. Performance is also evaluated under familiarity and match/mismatch with the ethnicity of observers. The findings of this study are used to develop an automated algorithm to verify the faces presented under disguise variations. We use automatically localized feature descriptors which can identify disguised face patches and account for this information to achieve improved matching accuracy. The performance of the proposed algorithm is evaluated on the IIIT-Delhi Disguise database that contains images pertaining to 75 subjects with different kinds of disguise variations. The experiments suggest that the proposed algorithm can outperform a popular commercial system and evaluates them against humans in matching disguised face images.
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Conceived and designed the experiments: TID RS MV AK. Performed the experiments: TID. Analyzed the data: TID RS MV. Contributed reagents/materials/analysis tools: TID. Wrote the paper: TID RS MV AK.
Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0099212