2013 |
Štruc, Vitomir; Gros, Jeneja Žganec; Dobrišek, Simon; Pavešić, Nikola Exploiting representation plurality for robust and efficient face recognition Proceedings Article V: Proceedings of the 22nd Intenational Electrotechnical and Computer Science Conference (ERK'13), str. 121–124, Portorož, Slovenia, 2013. Povzetek | Povezava | BibTeX | Oznake: competition, erk, face recognition, face verification, group evaluation, ICB, mobile biometrics, MOBIO, performance evaluation @inproceedings{ERK2013_Struc, The paper introduces a novel approach to face recognition that exploits plurality of representation to achieve robust face recognition. The proposed approach was submitted as a representative of the University of Ljubljana and Alpineon d.o.o. to the 2013 face recognition competition that was held in conjunction with the IAPR International Conference on Biometrics and achieved the best overall recognition results among all competition participants. Here, we describe the basic characteristics of the submitted approach, elaborate on the results of the competition and, most importantly, present some general findings made during our development work that are of relevance to the broader (face recognition) research community. |
Günther, Manuel; Costa-Pazo, Artur; Ding, Changxing; Boutellaa, Elhocine; Chiachia, Giovani; Zhang, Honglei; de Angeloni, Marcus Assis; Štruc, Vitomir; Khoury, Elie; Vazquez-Fernandez, Esteban; others, The 2013 face recognition evaluation in mobile environment Proceedings Article V: Proceedings of the IAPR International Conference on Biometrics (ICB), str. 1–7, IAPR 2013. Povzetek | Povezava | BibTeX | Oznake: biometrics, competition, face recognition, face verification, group evaluation, mobile biometrics, MOBIO, performance evaluation @inproceedings{gunther20132013, 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 UCHU, which learns optimal features with a convolutional neural network. Additionally, we assess the usability of the algorithms in mobile devices with limited resources. |
Objave
2013 |
Exploiting representation plurality for robust and efficient face recognition Proceedings Article V: Proceedings of the 22nd Intenational Electrotechnical and Computer Science Conference (ERK'13), str. 121–124, Portorož, Slovenia, 2013. |
The 2013 face recognition evaluation in mobile environment Proceedings Article V: Proceedings of the IAPR International Conference on Biometrics (ICB), str. 1–7, IAPR 2013. |