The 2013 face recognition evaluation in mobile environment

Author

Gunther, M. ; Costa-Pazo, A. ; Ding, Chibiao ; Boutellaa, E. ; Chiachia, Giovani ; Zhang, Haijun ; de Assis Angeloni, Marcus ; Struc, Vitomir ; Khoury, Elie ; Vazquez-Fernandez, E. ; Tao, Dacheng ; Bengherabi, Messaoud ; Cox, D. ; Kiranyaz, Serkan ; de Fr

fYear

2013

fDate

4-7 June 2013

Firstpage

1

Lastpage

7

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 8 different participants using two verification metrics. Most submitted algorithms rely on one 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 optimal features with a convolutional neural network. Additionally, we assess the usability of the algorithms in mobile devices with limited resources.

Keywords

Gabor filters; convolution; face recognition; feature extraction; image colour analysis; mobile computing; mobile handsets; neural nets; wavelet transforms; Gabor phases; Gabor wavelet responses; UC-HU; UNILJ-ALP; automatic face recognition evaluation; color information; convolutional neural network; face recognition algorithms; feature types; image representations; local binary patterns; mobile devices; mobile environment; unconstrained environments; Computational modeling; Face; Face recognition; Feature extraction; Histograms; Probes; Training;

fLanguage

English

Publisher

ieee

Conference_Titel

Biometrics (ICB), 2013 International Conference on

Conference_Location

Madrid

Type

conf

DOI

10.1109/ICB.2013.6613024

Filename

6613024