2013 |
Štruc, Vitomir; Gros, Jeneja Žganec; Dobrišek, Simon; Pavešić, Nikola Exploiting representation plurality for robust and efficient face recognition Proceedings Article In: Proceedings of the 22nd Intenational Electrotechnical and Computer Science Conference (ERK'13), pp. 121–124, Portorož, Slovenia, 2013. Abstract | Links | BibTeX | Tags: 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. |
2009 |
Poh, Norman; Chan, Chi Ho; Kittler, Josef; Marcel, Sebastien; McCool, Christopher; Argones-Rua, Enrique; Alba-Castro, Jose Luis; Villegas, Mauricio; Paredes, Roberto; Štruc, Vitomir; Pavešić, Nikola; Salah, Albert Ali; Fang, Hui; Costen, Nicholas Face Video Competition Proceedings Article In: Tistarelli, Massimo; Nixon, Mark (Ed.): Proceedings of the international Conference on Biometrics (ICB), pp. 715-724, Springer-Verlag, Berlin, Heidelberg, 2009. Abstract | Links | BibTeX | Tags: biometrics, competition, face recognition, face verification, ICB, performance evaluation @inproceedings{ICB2009, Person recognition using facial features, e.g., mug-shot images, has long been used in identity documents. However, due to the widespread use of web-cams and mobile devices embedded with a camera, it is now possible to realise facial video recognition, rather than resorting to just still images. In fact, facial video recognition offers many advantages over still image recognition; these include the potential of boosting the system accuracy and deterring spoof attacks. This paper presents the first known benchmarking effort of person identity verification using facial video data. The evaluation involves 18 systems submitted by seven academic institutes. |