Real-Time head pose estimation for mobile devices

Authors:
Euclides N. Arcoverde Neto;Rafael M. Barreto;Rafael M. Duarte;Joao Paulo Magalhaes;Carlos A. C. M. Bastos;Tsang Ing Ren;George D. C. Cavalcanti
Affiliations:
Center of Informatics, Federal University of Pernambuco, Brazil,C.E.S.A.R --- Recife Center for Advanced Studies and Systems, Brazil,Faculdade Boa Viagem, Brazil;Center of Informatics, Federal University of Pernambuco, Brazil,C.E.S.A.R --- Recife Center for Advanced Studies and Systems, Brazil;Center of Informatics, Federal University of Pernambuco, Brazil,C.E.S.A.R --- Recife Center for Advanced Studies and Systems, Brazil;Center of Informatics, Federal University of Pernambuco, Brazil;Center of Informatics, Federal University of Pernambuco, Brazil,C.E.S.A.R --- Recife Center for Advanced Studies and Systems, Brazil;Center of Informatics, Federal University of Pernambuco, Brazil;Center of Informatics, Federal University of Pernambuco, Brazil
Venue:
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Year:
2012

Citing 5
Cited 0

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Abstract

Mobile devices are an essential equipment in modern life. Nowadays, its presence is so widespread that almost everyone has a mobile phone, smartphone or tablet device. There are several different ways to interact with those equipments, such as the use of the keypad or the touchscreen. Here, we propose a real-time head pose estimation technique based on the secondary video camera as a means of interaction between the user and the device. The proposed technique is composed of several computer vision methods specially optimized to be able to operate in a restrict environment and a head pose estimation based on the calculations of the roll, yaw and pitch movements. Experiments were conducted based on 363 videos of 27 different people in a varied environment (illumination and background).