원문정보
초록
영어
Human gesture recognition is a non-verbal part for interaction or movement that can be used to involves real world and virtual world. In this paper, we explain a study on natural user interface (NUI) in human gesture recognition using RGB color information and depth information by Kinect camera from Microsoft Corporation. To achieve the goal, hand tracking and gesture recognition have no major dependencies of the work environment, lighting or users’ skin color, libraries of particular use for natural interaction and Kinect device, which serves to provide RGB images of the environment and the depth map of the scene were used. An improved CamShift tracking algorithm combined with depth information is used to tracking hand motion, and then an associative method of HMM and FNN is propose for gesture recognition step. The experimental results show out its good performance and it has higher stability and accuracy as well.
목차
1. Introduction
2. Hand Tracking by Using Improved Camshift Algorithm based on Depth Data
3. Feature Extraction and Gesture Recognition
3.1 Feature Extraction based on Orientation and Velocity
3.2 Gesture Recognition using HMM-FNN
4. Experimental Results
6. Conclusion
Acknowledgements
References