Robust face detection presents a difficult problem in real interaction scenarios, that, in order to achieve, most often requires employing additional sources of information. In this paper, we consider two such sources: Temporal information, available in the form of video sequences, and spatial information, available from multiple calibrated cameras with synchronous, overlapping fields of view of the 3D scene of interest. These two sources are exploited jointly, using a novel dynamic programming approach, for a lecture scenario inside appropriately equipped smart rooms, aiming at robust face detection of the lecturer within the available 2D camera views. Experimental results, reported on the CHIL project database, demonstrate that the proposed approach outperforms purely frame-based face detection.