Deducing the visual focus of attention from head pose estimation in dynamic multi-view meeting scenarios

This paper presents our work on recognizing the visual focus of attention during dynamic meeting scenarios. We collected a new dataset of meetings, in which acting participants were to follow a predefined script of events, to enforce focus shifts of the remaining, unaware meeting members. Including the whole room, all in all, a total of 35 potential focus targets were annotated, of which some were moved or introduced spontaneously during the meeting. On this dynamic dataset, we present a new approach to deduce the visual focus by means of head orientation as a first clue and show, that our system recognizes the correct visual target in over 57% of all frames, compared to 47% when mapping head pose to the first-best intersecting focus target directly.