Name
Abstract | ||
|---|---|---|
In this paper, we introduce a new vision based interaction technique for mobile phones. The user operates the interface by simply moving a finger in front of a camera. During these movements the finger is tracked using a method that embeds the Kalman filter and ExpectationMaximization (EM) algorithms. Finger movements are interpreted as gestures using Hidden Markov Models (HMMs). This involves first creating a generic model of the gesture and then utilizing unsupervised Maximum a Posteriori (MAP) adaptation to improve the recognition rate for a specific user. Experiments conducted on a recognition task involving simple control commands clearly demonstrate the performance of our approach. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-79547-6_26 | ICVS |
Keywords | Field | DocType |
hidden markov models,specific user,generic model,finger movement,adaptive motion-based gesture recognition,mobile phone,kalman filter,recognition rate,interaction technique,new vision,recognition task,handheld devices,hidden markov model,motion estimation,expectation maximization,finger tracking,user experience,human computer interaction,em algorithm,gesture recognition,handheld device | Computer vision,Interaction technique,Gesture,Computer science,Finger tracking,Gesture recognition,Kalman filter,Speech recognition,Mobile device,Artificial intelligence,Motion estimation,Hidden Markov model | Conference |
Volume | ISSN | ISBN |
5008 | 0302-9743 | 3-540-79546-4 |
Citations | PageRank | References |
2 | 0.38 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jari Hannuksela | 1 | 121 | 13.36 |
| Mark Barnard | 2 | 448 | 27.36 |
| pekka sangi | 3 | 56 | 6.18 |
| Janne Heikkilä | 4 | 2163 | 160.55 |