While there has been an enormous amount of research on face recognition under pose/illumination changes and image degradations, problems caused by occlusions are mostly overlooked. Moreover, most of the existing approaches of face recognition under occlusion conditions focus on overcoming facial occlusion problems due to sunglasses and scarf. To the best of our knowledge, occlusion due to cap has never been studied in the literature, but the importance of this problem should be emphasized since it is known that bank robbers and football hooligans take advantage of it for hiding their faces. This paper presents a solution to this newly identified face occlusion problem - the time-variant occlusion due to cap in entrance surveillance, in the context of face biometrics in video surveillance. The proposed approach consists of two parts: detection and tracking of occluded faces in complex surveillance videos; detecting the presence of cap by exploiting temporal information. The detection and tracking part is based upon body silhouette and elliptical head tracker. The classification of cap/non-cap faces utilizes dynamic time warping (DTW) and agglomerative hierarchical clustering. The proposed algorithm is evaluated on several surveillance videos and yields good detection rates.