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
Kumar A
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Dhamecha TI;Singh R;Vatsa M;Kumar A

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人脸验证虽然对人类来说是一项简单的任务,但却是一个长期开放的研究领域。这在很大程度上是因为具有挑战性的协变量,如伪装和老化,这使得准确核实一个人的身份变得非常困难。本文研究了伪装人脸识别/验证的人和机器性能。还根据对观察员族裔的熟悉程度和匹配/不匹配来评估业绩。这项研究的结果被用来开发一种自动算法来验证伪装变化下的人脸。我们使用自动局部化的特征描述符来识别伪装的人脸块,并考虑到这些信息,以提高匹配精度。在IIIT-德里伪装数据库上对所提算法的性能进行了评估,该数据库包含75个具有不同伪装变化的对象的图像。实验表明,该算法的性能优于一个流行的商业系统,并在匹配伪装人脸图像方面与人类进行了评估。
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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