Earticle

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

Abstract
 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

키워드

저자

• Wenkai Xu [ Department of Information & Communications Engineering, Tongmyong University ]
• Eung-Joo Lee [ Department of Information & Communications Engineering, Tongmyong University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605