A novel surveillance system integrating 2D and 3D facial data is presented in this paper, based on a low-cost sensor capable of real-time acquisition of 3D images and associated color images of a scene. Depth data is used for robust face detection, localization and 3D pose estimation, as well as for compensating pose and illumination variations of facial images prior to classification. The proposed system was tested under an open-set identification scenario for surveillance of humans passing through a relatively constrained area. Experimental results demonstrate the accuracy and robustness of the system under a variety of conditions usually encountered in surveillance applications.
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