Second screen interaction: an approach to infer tv watcher's interest using 3d head pose estimation

Julien Leroy, François Rocca, Matei Mancas, Bernard Gosselin

Abstract: In this paper, we present our "work-in-progress" approach to implicitly track user interaction and infer the interest a user can have for TV media. The aim is to identify moments of attentive focus, noninvasively and continuously, to dynamicaly improve the user profile by detecting which annotated media have drawn the user attention. Our method is based on the detection and estimation of face pose in 3D using a consumer depth camera. This allows us to determine when a user is or not looking at his television. This study is realized in the scenario of second screen interaction (tablet, smartphone), a behavior that has become common for spectators. We present our progress on the system and its integration in the LinkedTV project.