Face recognition from sketches using advanced correlation filters using hybrid eigenanalysis for face synthesis

Most face recognition systems focus on photo-based (or video) face recognition, but there are many law-enforcement applications where a police sketch artist composes a face sketch of the criminal and that is used by the officers to look for the criminal. Currently state-of-the-art research approach transforms all test face images into sketches then perform recognition in the sketch domain using the sketch composite, however there is one flaw in such approach which hinders it from being deployed fully automatic in the field, due to the fact that generating a sketch image from a surveillance footage will vary greatly due to illumination variations of the face in the footage under different lighting conditions. This will result imprecise sketches for real time recognition. In our approach we propose the opposite which is a better approach; we propose to generate a realistic face image from the composite sketch using a Hybrid subspace method and then build an illumination tolerant correlation filter which can recognize the person under different illumination variations. We show experimental results on our approach on the CMU PIE (Pose Illumination and Expression) database on the effectiveness of our novel approach.