Name
Title | ||
|---|---|---|
Hand gesture recognition and virtual game control based on 3D accelerometer and EMG sensors |
Abstract | ||
|---|---|---|
This paper describes a novel hand gesture recognition system that utilizes both multi-channel surface electromyogram (EMG) sensors and 3D accelerometer (ACC) to realize user-friendly interaction between human and computers. Signal segments of meaningful gestures are determined from the continuous EMG signal inputs. Multi-stream Hidden Markov Models consisting of EMG and ACC streams are utilized as decision fusion method to recognize hand gestures. This paper also presents a virtual Rubik's Cube game that is controlled by the hand gestures and is used for evaluating the performance of our hand gesture recognition system. For a set of 18 kinds of gestures, each trained with 10 repetitions, the average recognition accuracy was about 91.7% in real application. The proposed method facilitates intelligent and natural control based on gesture interaction. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1502650.1502708 | IUI |
Keywords | Field | DocType |
Accelero-meter,Electromyogram.,Gesture recognition,Human computer interaction | Computer vision,Decision fusion,Accelerometer,Gesture,Computer science,Gesture recognition,Virtual game,Speech recognition,Artificial intelligence,Hidden Markov model,Cube | Conference |
Volume | Issue | Citations |
null | null | 50 |
PageRank | References | Authors |
2.50 | 7 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xu Zhang | 1 | 390 | 37.49 |
| Xiang Chen | 2 | 90 | 6.78 |
| Wen-hui Wang | 3 | 56 | 4.97 |
| Ji-hai Yang | 4 | 226 | 13.30 |
| Vuokko Lantz | 5 | 333 | 20.79 |
| Kongqiao Wang | 6 | 634 | 43.95 |