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Ear recognition in a light field imaging framework: A new perspective

Moghaddam, A. ; Pereira, F. ; Correia, P.L.

IET Biometrics Vol. 7, Nº 3, pp. 224 - 231, May, 2018.

ISSN (print): 2047-4938
ISSN (online): 2047-4946

Scimago Journal Ranking: 0,37 (in 2018)

Digital Object Identifier: 10.1049/iet-bmt.2017.0204

Ear recognition is an emerging research area in image-based biometrics. The commercial availability of lenslet light field cameras able to capture full spatio-angular information has brought momentum to biometric and forensic research exploiting this new type of imaging sensors. This paper is the first to consider the usage of light field cameras for ear recognition, proposing both an appropriate content database and an ear recognition solution. The novel IST-EURECOM Lenslet Light Field Ear DataBase (LLFEDB) includes 536 light field images corresponding to four different poses, from 67 subjects, captured with a Lytro ILLUM lenslet light field camera. The IST-EURECOM LLFEDB includes critical cases such as ear images partly occluded by ear piercing, earing, hair and combination of occlusions. The novel light field based ear recognition solution proposed exploits the richer spatio-angular information available in the light field images. A comparative performance evaluation study using the IST-EURECOM LLFEDB, and focusing on the most recent light field and non-light field based descriptors for ear recognition, shows a very promising performance of the proposed descriptor, outperforming all the assessed descriptors.