Abstract
People often use non-linguistic communication methods such as physical gestures, which compose over 70% of our overall interaction with others. These physical gestures have regularity and repeatability as their common traits. This study is mainly discussing gesture recognition system for regular and repeated gestures. Torso PCA frame method is applied to angle transformation for such gesture recognition. In addition, a feature set is defined through extracting the patterns using envelope detection method and is applied to multi-layer perceptron for gesture recognition. For our experiment, skeletal structure was collected using Kinect, and 8 gestures were selected that people regularly use in real life. The recognition system was confirmed based on variety of people as our sample and the average accuracy was 89%.
| Original language | English |
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| Title of host publication | International Conference on Control, Automation and Systems |
| Publisher | IEEE Computer Society |
| Pages | 449-453 |
| Number of pages | 5 |
| ISBN (Electronic) | 9788993215069 |
| DOIs | |
| Publication status | Published - 16 Dec 2014 |
| Event | 2014 14th International Conference on Control, Automation and Systems, ICCAS 2014 - Gyeonggi-do, Korea, Republic of Duration: 22 Oct 2014 → 25 Oct 2014 |
Publication series
| Name | International Conference on Control, Automation and Systems |
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| ISSN (Print) | 1598-7833 |
Conference
| Conference | 2014 14th International Conference on Control, Automation and Systems, ICCAS 2014 |
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| Country/Territory | Korea, Republic of |
| City | Gyeonggi-do |
| Period | 22/10/14 → 25/10/14 |
Bibliographical note
Publisher Copyright:© 2014 Institute of Control, Robotics and Systems (ICROS).
Keywords
- Kinect
- body gesture recognition
- human robot Interaction(HRI)
- multi-layer perceptron(MLP)