To identify facial expressions accurately

we propose a precise local feature description method for facial expression recognition. First

the eyebrows

eyes

and mouth in a facial expression image are identified and extracted. The local features from the organ images are then obtained and processed by the expanded vector triangle pattern. The outline and detail features of the images can be statistic. Finally

different scales of sufficient vector triangle patterns are used to describe the features of the different organs. Various scales of sufficient vector triangle patterns are then combined to describe the features of the same organ. In this way

key organ information can be expressed fully. Experiments on the proposed method were performed using the JAFEE

Cohn-Kanade (CK)

and Pain Expressions database. The average recognition rates were 95.67%

97.83%

and 84.0%

and the average durations of feature extraction were 11.70 ms

30.23 ms

and 11.73 ms. The cross validation results showed that the precise local feature description method for facial expression recognition is fast and accurate. Through organ segmentation and the construction of flexible full vector triangle patterns

the precise local feature description method performs well in image feature description while consuming little time. The recognition results of the proposed method are better than those of the typical facial expression recognition method.