Competition on Counter Measures to 2-D Facial Spoofing Attacks

Murali Mohan Chakka;André Anjos;Sebastien Marcel;TRONCI, ROBERTO;Daniele Muntoni;Gianluca Fadda;Maurizio Pili;Nicola Sirena :Gabriele Murgia;Marco Ristori;ROLI, FABIO;Junjie Yan;Dong Yi;Zhen Lei;Zhiwei Zhang;Stan Li;William Robson Schwartz;Anderson Rocha;Helio Pedrini;Javier Lorenzo;Modesto Castrillon Santana;Jukka Määttä;Abdenour Hadid;Matti Pietikäinen

2011-01-01

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Abstract

Spoofing identities using photographs is one of the most common techniques to attack 2-D face recognition systems. There seems to exist no comparative studies of different techniques using the same protocols and data. The motivation behind this competition is to compare the performance of different state-of-the-art algorithms on the same database using a unique evaluation method. Six different teams from universities around the world have participated in the contest. Use of one or multiple techniques from motion, texture analysis and liveness detection appears to be the common trend in this competition. Most of the algorithms are able to clearly separate spoof attempts from real accesses. The results suggest the investigation of more complex attacks.