Light field local binary patterns description for face recognition
Light field cameras are emerging as powerful sensor devices to capture the full spatio-angular visual information in a viewing range. As more information should allow better analysis performance, this paper proposes a simple, yet effective descriptor, named Light Field Local Binary Patterns (LFLBP), able to exploit the richer information available in light field images for face recognition. The LFLBP descriptor combines two main components, the spatial, local LBP and the angular LBP, to capture not only the usual spatial information but also the light field angular information associated to the set of sub-aperture images, corresponding to different viewpoints. Experiments were conducted with the novel IST-EURECOM light field face database. When compared with competing methods, the proposed descriptor has shown superior face recognition performance under varied and challenging acquisition conditions. Moreover, the proposed light field angular LBP descriptor can be flexibly combined with any available spatial descriptor to derive combined descriptors for enhanced light field based face recognition performance.