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| Content Provider | Springer Nature Link |
|---|---|
| Author | Shimada, Atsushi Kawashima, Manabu Taniguchi, Rin ichiro |
| Copyright Year | 2011 |
| Abstract | We propose an approach to achieving early recognition of gesture patterns. Early recognition is a method for recognizing sequential patterns at their earliest stage. Therefore, in the case of gesture recognition, we can get a recognition result for human gestures before the gestures are finished. The most difficult problem in early recognition is knowing when the system has determined the result. Most traditional approaches suffer from this problem, since gestures are often ambiguous. At the start of a gesture, in particular, it is very difficult to determinate the recognition result since insufficient input data have been observed. Therefore, we have improved on the traditional approach by using a self-organizing map. |
| Starting Page | 198 |
| Ending Page | 201 |
| Page Count | 4 |
| File Format | |
| ISSN | 14335298 |
| Journal | Artificial Life and Robotics |
| Volume Number | 16 |
| Issue Number | 2 |
| e-ISSN | 16147456 |
| Language | English |
| Publisher | Springer Japan |
| Publisher Date | 2011-09-07 |
| Publisher Place | Japan |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Gesture recognition Early recognition Selforganizing map Computation by Abstract Devices Artificial Intelligence (incl. Robotics) Control, Robotics, Mechatronics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Biochemistry, Genetics and Molecular Biology |
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