Facial expression recognition using feature based techniques and model based techniques: A survey

Abstract

Facial expression is a way of non-verbal communication. A person depicts his/her feelings through facial expressions. In computer systems facial expressions help in verification, identification and authentication. One popular use of facial expression recognition is automatic feedback capture from customers upon reacting to a particular product. Effective recognition technology is in high demand by the common users of today's gadgets and technologies. Facial expression recognition technique is broadly classified into two techniques: Feature based techniques and Model based techniques. The key contribution of this article is that we have analyzed latest state of the art techniques in Feature based techniques and Model based techniques. These techniques are analyzed using various standard public face databases: GEMEP-FERA, BU-3DFE, CK+, Bosphorous, MMI, JAFFE, LFW, FERET, CMU-PIE, Georgia tech, AR, eNTERFACE 05 and FRGC. From our analysis we found that for Feature based Curvelet approach performed on FRGCv2 database gave an excellent 97.83% recognition rate and Model based textured 3D video technique performed on BU-4DFE database gave an excellent 94.34 % recognition rate.