Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/36233
Title: Recognizing disguised faces : human and machine evaluation
Authors: Dhamecha, TI
Singh, R
Vatsa, M
Kumar, A 
Issue Date: 2014
Publisher: Public Library of Science
Source: PLoS one, 2014, v. 9, no. 7, e99212 How to cite?
Journal: PLoS one 
Abstract: 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.
URI: http://hdl.handle.net/10397/36233
EISSN: 1932-6203
DOI: 10.1371/journal.pone.0099212
Rights: © 2014 Dhamecha et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The following publication: Dhamecha TI, Singh R, Vatsa M, Kumar A (2014) Recognizing Disguised Faces: Human and Machine Evaluation. PLoS ONE 9(7): e99212 is available at https://doi.org/10.1371/journal.pone.0099212
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