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A Method for Controlling Wheelchair Using Hand Gesture Recognition

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Book cover Robot Intelligence Technology and Applications 2012

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 208))

Abstract

This paper presents an approach for controlling wheelchair movement using hand gesture recognition. This method was developed based on the curvature of a hand shapes contour. It is simple and has some features to recognize and offers robustness recognizing gestures of one hand. The curvature based hand gesture recognition algorithms recognizes hand gestures using a combination of hand shape contour geometry and calculating the distance from the center of hand to the convex hull on the fingertips. In this paper, this method is able to recognize 5 different hand gestures in same backgrounds for five status movement of wheelchair like as: forward, reverse, left, right and stop. Experiments are presented to show that the wheelchair is able to move and avoid obstacles autonomously while controlled by its user via the hand gesture.

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References

  1. Pavlovic, V., Sharma, R., Huang, T.: Visual interpretation of hand gestures for human–computer interaction: a review. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 677–695 (1997)

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  2. Tien, N.K., Thinh, N.T.: Using Electrooculogram and Electromyogram for powered wheelchair. In: IEEE ROBIO 2011 - International Conference on Robotics and Biomimetics, pp. 1585–1590 (2011)

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  3. Kang, S.-P., Katupitiya, J.: A hand gesture controlled semi-autonomous wheelchair. In: Intelligent Robots and Systems (IRON 2004), vol. 4, pp. 3565–3570 (2004)

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  4. Kathuria, P.: Hand Gesture Recognition. Japan Advanced Institute of Science and Technology (2011)

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Correspondence to Nguyen Kim-Tien .

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© 2013 Springer-Verlag Berlin Heidelberg

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Kim-Tien, N., Truong-Thinh, N., Cuong, T.D. (2013). A Method for Controlling Wheelchair Using Hand Gesture Recognition. In: Kim, JH., Matson, E., Myung, H., Xu, P. (eds) Robot Intelligence Technology and Applications 2012. Advances in Intelligent Systems and Computing, vol 208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37374-9_93

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  • DOI: https://doi.org/10.1007/978-3-642-37374-9_93

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37373-2

  • Online ISBN: 978-3-642-37374-9

  • eBook Packages: EngineeringEngineering (R0)

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