Multi-camera head pose estimation

Estimating people's head pose is an important problem, for which many solutions have been proposed. Most existing solutions are based on the use of a single camera and assume that the head is confined in a relatively small region of space. If we need to estimate unintrusively the head pose of persons in a large environment, however, we need to use several cameras to cover the monitored area. In this work, we propose a novel solution to the multi-camera head pose estimation problem that exploits the additional amount of information that provides multi-camera configurations. Our approach uses the probability estimates produced by multi-class support vector machines to calculate the probability distribution of the head pose. The distributions produced by the cameras are fused, resulting in a more precise estimate than the one provided individually. We report experimental results that confirm that the fused distribution provides higher accuracy than the individual classifiers and a high robustness against errors.

Yeguas-Bolivar, E. (författare)
Saffiotti, AlessandroÖrebro universitet,Institutionen för naturvetenskap och teknik(Swepub:oru)asaffio (författare)
Medina-Carnicer, R. (författare)
Örebro universitetInstitutionen för naturvetenskap och teknik (creator_code:org_t)

Ingår i:Machine Vision and Applications: Springer23:3, s. 479-4900932-80921432-1769

Av författaren/redakt...: Munoz-Salinas, R ...; Yeguas-Bolivar, ...; Saffiotti, Aless ...; Medina-Carnicer, ...

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