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The 2013 Face Recognition Evaluation in Mobile Environment
Type of publication: Idiap-RR
Citation: Gunther_Idiap-RR-36-2013
Number: Idiap-RR-36-2013
Year: 2013
Month: 11
Institution: Idiap
Abstract: Automatic face recognition in unconstrained environments is a challenging task. To test current trends in face recognition algorithms, we organized an evaluation on face recognition in mobile environment. This paper presents the results of eight different participants using two verification metrics. Most submitted algorithms rely on on or more of three types of features: local binary patterns, Gabor wavelet responses including Gabor phases, and color information. The best results are obtained from UNILJ-ALP, which fused several image representations and feature types, and UC-HU, which learns ptimal features with a convolutional neural network. Additionally, we assess the usability of the algorithms in mobile devices with limited resources.
Projects Idiap
Authors Günther, Manuel
Costa-Pazo, Artur
Ding, Changxing
Boutellaa, Elhocine
Chiachia, Giovani
Zhang, Honglei
de Assis Angeloni, Marcus
Struc, Vitomir
Khoury, Elie
Vazquez-Fernandez, Esteban
Tao, Dacheng
Bengherabi, Messaoud
Cox, David
Kiranyaz, Serkan
de Freitas Pereira, Tiago
Zganec-Gros, Jerneja
Argones-Rúa, Enrique
Pinto, Nicolas
Gabbouj, Moncef
Simões, Flávio
Dobrisek, Simon
González-Jiménez, Daniel
Rocha, Anderson
Uliani Neto, Mário
Pavesic, Nikola
Falcão, Alexandre
Violato, Ricardo
Marcel, Sébastien
Crossref by Gunther_ICB2013_2013
Added by: [ADM]
Total mark: 0
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