Abstract
The aim of this paper is to present a methodology for hand detection, propose a finger detection method, and finally apply them to posture recognition. The detected hand and finger can be used to implement the non-contact mouse. This technology can be used to control home devices such as curtain and television. Skin color is used to segment the hand region from the background, and counter is extracted from the segmented hand. The counter analysis of gives us the location of fingertip in the hand. Fingertip tracking is performed assuming a constant velocity model and using a pixel labeling approach. From the tracking process, we extract several hand features that are fed to a finite state classifier that identifies the hand configuration. The hand can be classified into many gesture classes or several different movement directions. This method of skin segmentation assumes that the background does not contain any skin colored object beside hands. We have performed an extensive experiment and achieved a very encouraging result. Ultimately, this paper suggests an empirical application to verify the adequacy and validity of the proposed systems. Accordingly, the satisfaction and quality of services will improved gesture recognition.
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Acknowledgements
This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research Center) support program supervised by the NIPA(National IT Industry Promotion Agency)” (NIPA-2011-C1090-1131-0004)
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Kang, SK., Chung, KY., Rim, KW., Lee, JH. (2012). Development of Real-Time Gesture Recognition System Using Visual Interaction. In: Kim, K., Ahn, S. (eds) Proceedings of the International Conference on IT Convergence and Security 2011. Lecture Notes in Electrical Engineering, vol 120. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2911-7_25
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DOI: https://doi.org/10.1007/978-94-007-2911-7_25
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