By Topic

Research on algorithm of state recognition of students based on facial expression

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Zhou Changjun ; Dept. of Comput. Technol., Shanghai Jiao Tong Univ., Shanghai, China ; Peipei Shen ; Xiong Chen

Facial expression recognition has become one important research direction in HCI area, because facial expression can effectively reflect the inner emotion of people. In some areas (e.g. remote education), expression recognition system, as an auxiliary tool, is used to analyze mental states of students and plays an important role. In this paper, we developed a student-state recognition system based on facial expression. We improved local binary pattern (LBP) into an algorithm that based on specific area to extract facial features, and presented features with LBP histograms of expression image. Finally, support vector machine and nearest neighbor classification are combined to classify expressions, then classify the mental states of students based on expression. We conducted experiments with samples from a Japanese female facial expression database. Our study obtained an average facial expression recognition rate of 71.35%. High accuracy and real-time make the system applied in classroom well to recognize mental states of students.

Published in:

Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on  (Volume:2 )

Date of Conference:

12-14 Aug. 2011