Name
Title | ||
|---|---|---|
Towards academic affect modeling through experimental hybrid gesture recognition algorithm |
Abstract | ||
|---|---|---|
The identification of learner engagement is an important aspect of assessment. Aside from facial expressions, gesture is a key feature in the identification of student engagement. The costly video invigilation during assessment shows the need to find other ways to define student engagement during an online examination. For this purpose, this study proposed gesture modeling to classify and identify affect. The research defines student disengagement affect using head poses as gesture during the online examination. The divide-and-conquer algorithm implementation on object detection using Haar Cascade feature extraction and HMM classification resulted in 78.77% accuracy level to classify disengaged behavior during an online examination. The experimental results show that head-poses when properly modeled can be used to define affect as applied to examination behavior. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3239283.3239305 | international conference data science |
Field | DocType | Citations |
Object detection,Gesture,Computer science,Gesture recognition,Algorithm,Haar-like features,Feature extraction,Facial expression,Student engagement,Hidden Markov model | Conference | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mideth B. Abisado | 1 | 0 | 0.34 |
| Bobby D. Gerardo | 2 | 27 | 13.79 |
| Larry A. Vea | 3 | 0 | 0.68 |
| Ruji P. Medina | 4 | 0 | 3.38 |