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

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Abstract: 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.

Keywords: Gesture Recognition, Depth Image, Time of Flight REFERENCES [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 2.4.6.0 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

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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

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