Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park



Space Gesture Recognition System Implementation

pdf PDF


This paper introduces a hand gesture recognition system that can detect both of a user’s hands, using depth data generated through an infrared Time of Flight (TOF) method combined with a depth camera. Noise removal using expansion, erosion, and median filters, and hand recognition using integrated images, are applied to create a gesture recognition system that can detect both hands. Both hardware and software necessary for actual testing were gathered, and the recognition speed and accuracy were measured.


Gesture Recognition, Depth Image, Time of Flight


[1] I. F. Ince, M. S. Garzon, and T. C. Yang, "Hand Mouse: Real time hand motion detection system based on analysis of finger blobs", International Journal of Digital Technology and its Applications, Vol. 4, No. 2, pp. 40-56, 2010.

[2] S. Koepnick, R. V. Hoang, M. R. Sgambati, D. S. Coming, E. A. Suma, and W. R. Sherman, "RIST: Radiological Immersive Survey Training for Two Simultaneous Users", Computers & Graphics Special Issue on Graphics for Serious Games, Vol.34, No. 6, pp. 665-676, 2010.

[3] Intel Corporation. Open Source Computer Vision Library reference manual. December 2000.

[4] Y. Hirobe, T.Niikura, Y. Watanabe, T. Komuro,M. Ishikawa, “Vision-based Input Interface for Mobile Devices with High-speed Fingertip Tracking,“ Adj. Proc. ACM UIST 2009, pp. 7-8.

[5] OpenCV documentation. http://docs.opencv.org/

Cite this paper

Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park. (2018) Space Gesture Recognition System Implementation. International Journal of Signal Processing, 3, 1-4


Copyright © 2018 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0