Classifying student's faces for teaching assistant system
This paper describes the facial emotion recognition to determine the student's conditions. The facial emotion recognition could be envisioned to sense the student's attention state through a CCD camera. Therefore, facial images were analyzed to extract the features to characterize the vari...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Published: |
2010
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/3569/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This paper describes the facial emotion recognition to determine the student's conditions. The facial emotion recognition could be envisioned to sense the student's attention state through a CCD camera. Therefore, facial images were analyzed to extract the features to characterize the variations between two categories of student's faces (understand or unsure/confused) images. The features extraction techniques apply was Principal Component Analysis (PCA), this algorithm finds the principle components of the covariance matrix of a set of face images. Then, the eigenvalues component will be used as an input to the Minimum Distance classifier. The ultimate goal of this research is to develop an intelligent system to investigate the relation between teaching quality contents and comprehension in learning according to the specific emotion state. |
|---|