View based approach to forensic face recognition

Face recognition is a challenging problem for surveillance view images commonly encountered in a forensic face recognition case. One approach to deal with a non-frontal test image is to synthesize the corresponding frontal view image and compare it with frontal view reference images. However, it is often difficult to synthesize a good quality frontal view image from a surveillance video because the test image is usually of low quality. In this paper, we investigate if it is useful to instead transform the reference images so that it matches the pose, illumination and camera of the surveillance view test image. This approach, also called the view based approach, ensures that a face recognition system always gets to compare images having a similar, not necessarily the frontal, view. Our results with surveillance view images captured 6 months apart (taken from the MultiPIE data set) and using five different face recognition systems show that improved recognition performance under surveillance conditions can be attained by exactly matching the pose, illumination and camera between the test and reference images