Recognizing disguised faces: human and machine evaluation.
Recognizing disguised faces: human and machine evaluation.
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DOI:
10.1371/journal.pone.0099212
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发表时间:
2014
期刊:
影响因子:
3.7
通讯作者:
Kumar A
中科院分区:
文献类型:
--
作者:
Dhamecha TI;Singh R;Vatsa M;Kumar A
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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