%0 Conference Proceedings
%T Real-Time Face Detection and Tracking Utilising OpenMP and ROS
%A Eduardo Tusa
%A Arash Akbarinia
%A Raquel Gil Rodriguez
%A Corina Barbalata
%B 3rd Asia-Pacific Conference on Computer Aided System Engineering
%D 2015
%F Eduardo Tusa2015
%O NEUROBIT
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2659), last updated on Thu, 12 May 2016 17:37:07 +0200
%X The first requisite of a robot to succeed in social interactions is accurate human localisation, i.e. subject detection and tracking. Later, it is estimated whether an interaction partner seeks attention, for example by interpreting the position and orientation of the body. In computer vision, these cues usually are obtained in colour images, whose qualities are degraded in ill illuminated social scenes. In these scenarios depth sensors offer a richer representation. Therefore, it is important to combine colour and depth information. Thesecond aspect that plays a fundamental role in the acceptance of social robots is their real-time-ability. Processing colour and depth images is computationally demanding. To overcome this we propose a parallelisation strategy of face detection and tracking based on two different architectures: message passing and shared memory. Our results demonstrate high accuracy inlow computational time, processing nine times more number of frames in a parallel implementation. This provides a real-time social robot interaction.
%K RGB-D
%K Kinect
%K Human Detection and Tracking
%K ROS
%K OpenMP
%U http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7281992
%U http://refbase.cvc.uab.es/files/TAG2015.pdf
%U http://dx.doi.org/10.1109/APCASE.2015.39
%P 179-184