지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2014.10
- 수록면
- 449 - 453 (5page)
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초록· 키워드
오류제보하기
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%.
목차
Abstract
1. INTRODUCTION
2. GESTURE FEATURE REPRESENTATION
3. GESTURE RECOGNITION WITH MLP
4. EXPERIMENT AND RESULT
4. CONCLUSION
REFERENCES
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