Proceedings of the Korea Contents Association Conference (한국콘텐츠학회:학술대회논문집)
- 2016.05a
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- Pages.11-12
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- 2016
Research of Gesture Recognition Technology Based on GMM and SVM Hybrid Model Using EPIC Sensor
EPIC 센서를 이용한 GMM, SVM 기반 동작인식기법에 관한 연구
- CHEN, CUI (Chonnam National Univ) ;
- Kim, Young-Chul (Chonnam National Univ)
- Published : 2016.05.20
Abstract
SVM (Support Vector machine) is powerful machine-learning method, and obtains better performance than traditional methods in the applications of muti-dimension nonlinear pattern classification. For the case of SVM model training and low efficiency in large samples, this paper proposes a combination of statistical parameters of the GMM-UBM (Universal Background Model) model. It is very effective to solve the problem of the large sample for the SVM training. The experiment is carried on four special dynamic hand gestures using the EPIC sensors. And the results show that the improved dynamic hand gesture recognition system has a high recognition rate up to 96.75%.
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