DocumentCode
3696104
Title
Concentration analysis by detecting face features of learners
Author
Seunghui Cha;Wookhyun Kim
Author_Institution
Dept. of Computer Engineering, Yeungnam University, Gyungsan, Korea
fYear
2015
Firstpage
46
Lastpage
51
Abstract
The paper presents an analysis on the concentration of learning. By capturing video images of students, the proposed method detects and analyzes facial features from the image data and determines the state of learner´s concentration. Since the concentration is important to the learners, this method is applied to the classrooms. First, feature points are generated from the face and then feature points of the face are used to determine non-focused state. The length of the front face is used to make a decision for the face change. The coordinate value of the facial center is used to decide the face turns. The criteria value of the opened eye is used to decide whether the closed eyes or the opened eyes. Through the experiments, the proposed method detects the concentration up to 90%.
Keywords
"Face","Feature extraction","Mathematical model","Algorithm design and analysis","Face recognition","Face detection","Classification algorithms"
Publisher
ieee
Conference_Titel
Communications, Computers and Signal Processing (PACRIM), 2015 IEEE Pacific Rim Conference on
Electronic_ISBN
2154-5952
Type
conf
DOI
10.1109/PACRIM.2015.7334807
Filename
7334807
Link To Document