Abstract
This paper proposes a hand gesture recognition technique that allows users to enjoy uninterrupted interaction with a variety of multimedia applications. Hand gestures are recognized using joint information acquired from a Kinect sensor, and the recognized gestures are applied to multimedia content. To this end, hand gestures are quantized in the grid space, expressed using an 8-directional vector chain, and finally recognized on the basis of a hidden Markov model. To assess the proposed approach, we define the hand gestures used in the “Smart Interior” multimedia application, and collect a dataset of gestures using the Kinect. Our experiments demonstrate a high recognition ratio of between 90 and 100 %. Furthermore, the experiments identify the possibility of applying this approach to a variety of multimedia content by verifying its superior operation in actual applications.
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Acknowledgments
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (NIPA-2014-H0301-14-1021) supervised by the NIPA (National IT Industry Promotion Agency).
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Lee, S., Sim, S., Um, K., Jeong, YS., Cho, K. (2015). Hand Gesture Recognition Using 8-Directional Vector Chains in Quantization Space. In: Park, J., Pan, Y., Chao, HC., Yi, G. (eds) Ubiquitous Computing Application and Wireless Sensor. Lecture Notes in Electrical Engineering, vol 331. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9618-7_31
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DOI: https://doi.org/10.1007/978-94-017-9618-7_31
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