Human-Computer Natur al User Inter face Based on Hand Motion Detection and Tracking

  • Xu, Wenkai (Dept. of Information Communication Engineering, Tongmyong University) ;
  • Lee, Eung-Joo (Dept. of Information Communication Engineering, Tongmyong University)
  • Received : 2011.03.23
  • Accepted : 2011.06.01
  • Published : 2012.04.30


Human body motion 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 hand motion 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 is used to tracking hand motion, the experimental results show out it has better performance than Camshift algorithm, and it has higher stability and accuracy as well.


Supported by : NIPA


  1. Valli. A., "The Design of Natural Interaction," Multimedia Tools Appl. Vol.38, No.3, pp. 295-305, 2008
  2. Valli. A., Notes on Natural Interaction,, 2005.
  3. Javier Calle, Paloma Martínez, David del Valle, and Dolores Cuadra. "Towards the Achievement of Natural Interaction," Engineering and the User Interface, pp. 1-19, 2009.
  4. Del Bimbo, A., "Special Issue on Natural Interaction," Multimedia Tools and Applications, Vol.38, No.3, pp. 293-294, 2008.
  5. Kinect Ads: You Are the Controller, 2010/oct10/10-21kinectads.mspx, 2011.
  6. J. Giles, "Inside the race to hack the Kinect," The New Scientist, Vol.208, No.2789, pp. 22-23, 2010.
  7. Open Kinect imaging information,, 2010.
  8. Ros Kinect calibration,, 2011.
  9. Matthew Fisher, Kinect study,˜mdfisher/Kinect.html, 2010.
  10. Wenkai Xu and Eung-Joo Lee, "Hand Gesture Recognition using Improved Hidden Models," Journal of Korea Multimedia Society, Vol.14, No.7, pp. 866-871, 2011.
  11. Wenkai Xu and Eung-Joo Lee, "Gesture Recognition Based on 2D and 3D Feature by using Kinect Device," International Conference on Infromation and Security Assurance, Vol.6, No.1, April.28-30, 2012

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