Face recognition "on the move" combining incomplete information

Face recognition has a strong potential for identity verification on mobile devices, now embedding high resolution cameras and high-end computing hardware. Personal computing devices often also embed automatic face detection, thus facilitating the extraction and processing of face data. The main objective of this paper is to implement a flexible architecture to recognize faces from partial face data. The proposed architecture can be very effective to analyze video data from forensic cases where portions of the face are hidden from other objects. The proposed approach is based on the application of Kernel Fisher Analysis (KFA) to Gabor features extracted from the available face data. Several experiments carried out on realistic image samples demonstrate the validity of the proposed approach.