In this paper, we present a detailed analysis of the face recognition problem in smart room environment. We first examine the well-known face recognition algorithms in order to observe how they perform on the images collected under such environments. Afterwards, we investigate two aspects of doing face recognition in a smart room. These are: utilizing the images captured by multiple fixed cameras located in the room and handling possible registration errors due to the low resolution of the aquired face images. In addition, we also provide comparisons between frame-based and video-based face recognition and analyze the effect of frame weighting. Experimental results obtained on the CHIL database, which has been collected from different smart rooms, show that benefiting from multi-view video data and handling registration errors reduce the false identification rates significantly.
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