Robust stereoscopic head pose estimation in human-computer interaction and a unified evaluation framework

  • Authors:

  • Georg Layher;Hendrik Liebau;Robert Niese;Ayoub Al-Hamadi;Bernd Michaelis;Heiko Neumann

  • Affiliations:

  • University of Ulm, Institute of Neural Information Processing;University of Ulm, Institute of Neural Information Processing;Otto-von-Guericke University Magdeburg, IESK;Otto-von-Guericke University Magdeburg, IESK;Otto-von-Guericke University Magdeburg, IESK;University of Ulm, Institute of Neural Information Processing

  • Venue:
  • ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
  • Year:
  • 2011

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Abstract

The automatic processing and estimation of view direction and head pose in interactive scenarios is an actively investigated research topic in the development of advanced human-computer or human-robot interfaces. Still, current state of the art approaches often make rigid assumptions concerning the scene illumination and viewing distance in order to achieve stable results. In addition, there is a lack of rigorous evaluation criteria to compare different computational vision approaches and to judge their flexibility. In this work, we make a step towards the employment of robust computational vision mechanisms to estimate the actor's head pose and thus the direction of his focus of attention. We propose a domain specific mechanism based on learning to estimate stereo correspondences of image pairs. Furthermore, in order to facilitate the evaluation of computational vision results, we present a data generation framework capable of image synthesis under controlled pose conditions using an arbitrary camera setup with a free number of cameras. We show some computational results of our proposed mechanism as well as an evaluation based on the available reference data.