Effects of sample stretching in face recognition

Face stretching is something that can occur intentionally and unintentionally when preparing a face sample for enrollment in a face recognition system. In this paper we assess what affects both horizontal and vertical stretching have on a face recognition algorithms. Basic closed-set identification tests revealed that holistic face recognition algorithms performed poorly compared to feature based recognition algorithms when classifying non-stretched samples against templates based on stretched samples.