Abstract
Existing engagement estimation methods only show discrete estimation results according to the degree of engagement, and do not express fine-grained state information of the object. In this paper, we propose a continuous engagement estimation framework using estimated gaze direction and facial expression information. Also, we build a video-based engagement estimation database and succeeded in qualitatively verifying the performance of our framework.
| Original language | English |
|---|---|
| Title of host publication | ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 937-939 |
| Number of pages | 3 |
| ISBN (Electronic) | 9781665485593 |
| DOIs | |
| State | Published - 2022 |
| Event | 37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022 - Phuket, Thailand Duration: 5 Jul 2022 → 8 Jul 2022 |
Publication series
| Name | ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications |
|---|
Conference
| Conference | 37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022 |
|---|---|
| Country/Territory | Thailand |
| City | Phuket |
| Period | 5/07/22 → 8/07/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.
Keywords
- engagement estimation
- facial expression
- gaze