Name
Abstract | ||
|---|---|---|
We introduce an immersive system prototype that integrates face, gesture and speech recognition techniques to support multi-modal human-computer interaction capability. Embedded in an indoor room setting, a multi-camera system is developed to monitor the user facial behavior, body gesture and spatial location in the room. A server that fuses different sensor inputs in a time-sensitive manner so that our system knows who is doing what at where in real-time. When correlating with speech input, the system can better understand the user intention for interaction purpose. We evaluate the performance of core recognition techniques on both benchmark and self-collected datasets and demonstrate the benefit of the system in various use cases. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/FG.2018.00083 | 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018) |
Keywords | Field | DocType |
human-computer interaction system,multi-modal sensor fusion | Use case,Gesture,Computer science,Human–computer interaction,Immersion (virtual reality),Fuse (electrical),Modal | Conference |
ISSN | ISBN | Citations |
2326-5396 | 978-1-5386-2336-7 | 2 |
PageRank | References | Authors |
0.40 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rui Zhao | 1 | 15 | 4.76 |
| Kang Wang | 2 | 25 | 10.98 |
| Rahul R. Divekar | 3 | 4 | 3.27 |
| Robert Rouhani | 4 | 2 | 0.40 |
| Hui Su | 5 | 293 | 33.30 |
| Qiang Ji | 6 | 2780 | 168.90 |