Real-Time Face Detection and Tracking Utilising OpenMP and ROS

Eduardo Tusa, Arash Akbarinia, Raquel Gil Rodriguez, Corina Barbalata

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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. The second 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 in low computational time, processing nine times more number of frames in a parallel implementation. This provides a real-time social robot interaction.

Original languageEnglish
Title of host publication2015 Asia-Pacific Conference on Computer Aided System Engineering (APCASE)
Number of pages6
ISBN (Print)9781479975884
Publication statusPublished - 2015
EventAsia-Pacific Conference on Computer-Aided System Engineering 2015 - Quito, Pichincha, Ecuador
Duration: 14 Jul 201516 Jul 2015


ConferenceAsia-Pacific Conference on Computer-Aided System Engineering 2015
Abbreviated titleAPCASE 2015
CityQuito, Pichincha


  • Human Detection and Tracking
  • Kinect
  • OpenMP
  • RGB-D
  • ROS

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Control and Systems Engineering


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