Method of Facial Expression Recognition Based on Coarse-to-fine Classification
Xiaoyi Feng · Jisuanji gongcheng · 2007
This paper presents an effective method for facial expression recognition.It analyzes seven basic expressions: angry,disgust,fear,happiness,neutral,sadness and surprise.The local binary pattern(LBP) operator is used to extract face appearance features.A two-stage classification method is proposed.At the first(coarse classification) stage,two expression candidates from initial seven are selected.At the second(fine classification) stage,one of the two candidate classes is verified as final expression class by the Chi square statistic.Our algorithm is tested on the Jaffe database and the recognition rate for a new person’s expression is 77.9%,which is higher than all the other reported methods.