DocumentCode :
2422154
Title :
Mitigating effects of plastic surgery: Fusing face and ocular biometrics
Author :
Jillela, Raghavender ; Ross, Arun
Author_Institution :
West Virginia Univ., Morgantown, WV, USA
fYear :
2012
fDate :
23-27 Sept. 2012
Firstpage :
402
Lastpage :
411
Abstract :
The task of successfully matching face images obtained before and after plastic surgery is a challenging problem. The degree to which a face is altered depends on the type and number of plastic surgeries performed, and it is difficult to model such variations. Existing approaches use learning based methods that are either computationally expensive or rely on a set of training images. In this work, a fusion approach is proposed that combines information from the face and ocular regions to enhance recognition performance in the identification mode. The proposed approach provides the highest reported recognition performance on a publicly accessible plastic surgery database, with a rank-one accuracy of 87.4%. Compared to existing approaches, the proposed approach is not learning based and reduces computational requirements. Furthermore, a systematic study of the matching accuracies corresponding to various types of surgeries is presented.
Keywords :
biometrics (access control); face recognition; image fusion; image matching; surgery; face biometrics; face image matching; face region; fusion approach; identification mode; information combination; learning based method; matching accuracy; ocular biometrics; ocular region; plastic surgery database; plastic surgery effects mitigating; recognition performance enhancement; Accuracy; Biometrics (access control); Databases; Face; Face recognition; Feature extraction; Surgery;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biometrics: Theory, Applications and Systems (BTAS), 2012 IEEE Fifth International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
978-1-4673-1384-1
Electronic_ISBN :
978-1-4673-1383-4
Type :
conf
DOI :
10.1109/BTAS.2012.6374607
Filename :
6374607
Link To Document :
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