원문정보
보안공학연구지원센터(IJSIP)
International Journal of Signal Processing, Image Processing and Pattern Recognition
vol.3 no.1
2010.03
pp.37-50
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In this paper, we present our results of automatic gesture recognition systems using different types of cameras in order to compare them in reference to their performances in segmentation. The acquired image segments provide the data for further analysis. The images of a single camera system are mostly used as input data in the research area of gesture recognition. In comparison to that, the analysis results of a stereo color camera and a thermal camera system are used to determine the advantages and disadvantages of these camera systems. On this basis, a real-time gesture recognition system is proposed to classify alphabets (A-Z) and numbers (0-9) with an average recognition rate of 98% using Hidden Markov Models (HMM).
목차
Abstract
1. Introduction
2. Gesture recognition system
2.1 Data gathering and evaluation
2.2. Segmentation
2.3. Evaluation of segmentation results
2.4. Feature extraction
2.5. Classification
3. Experimental results
4. Summary and conclusion
5. Acknowledgments
References
1. Introduction
2. Gesture recognition system
2.1 Data gathering and evaluation
2.2. Segmentation
2.3. Evaluation of segmentation results
2.4. Feature extraction
2.5. Classification
3. Experimental results
4. Summary and conclusion
5. Acknowledgments
References
키워드
저자정보
참고문헌
자료제공 : 네이버학술정보