A new framework for face recognition in and beyond the visible spectrum

This work present a framework for the evaluation of face recognition performances in and beyond the visible spectrum. A new multispectral face database was developed and includes visible and different infrared spectrums. Face extraction and normalization techniques are introduced and used to normalize face images from the Laval University and Equinox databases. This framework propose different face learning and recognition techniques. Also, Texture space transformations are implemented and can be used prior to face learning and recognition. Finally, multi-scale fusion algorithms are present in this framework and can be used for the evaluation of fusion schemes in multispectral face recognition.