Head pose estimation & TV Context: current technology

Abstract

With the arrival of low-cost high quality cameras, implicit user behaviour tracking is easier and it becomes very interesting for viewer modelling and content personalization in a TV context. In this paper, we present a comparison between three common algorithms of automatic head direction extraction for a person watching TV in a realistic context. Those algorithms compute the different rotation angles of the head (pitch, roll, yaw) in a non-invasive and continuous way based on 2D and/or 3D features acquired with low cost cameras. These results are compared with a reference based on the Qualisys motion capture commercial system which is a robust marker-based tracking system. The performances of the different algorithms are compared function of different configurations. While our results show that full implicit behaviour tracking in real-life TV setups is still a challenge, with the arrival of next generation sensors (as the new Kinect one sensor), accurate TV personalization based on implicit behaviour is close to become a very interesting option.

Keywords

• head pose estimation
• viewer interest
• face direction
• Qualisys
• Kinect
• face tracking
• 3D point cloud