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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/93444


    Title: A Real Time Hand Gesture Recognition System Based on DFT and SVM
    Authors: Chen, Wen-Her;Hsieh, Ching-Tang;Liu, Tsun-Te
    Contributors: 淡江大學電機工程學系
    Keywords: BEA;Camshift;Hand Gesture Recognition;Support Vector Machine;SVM
    Date: 2013-01
    Issue Date: 2014-01-10 13:35:26 (UTC+8)
    Publisher: Stafa-Zurich: Trans Tech Publications Ltd.
    Abstract: Vision based band gesture recognition provides a more nature and powerful means for human-computer interaction. A fast detection process of hand gesture and an effective feature extraction process are presented. The proposed a hand gesture recognition algorithm comprises four main steps. First use Cam-shift algorithm to track skin color after closing process. Second, in order to extract feature, we use BEA to extract the boundary of the hand. Third, the benefits of Fourier descriptor are invariance to the starting point of the boundary, deformation, and rotation, and therefore transform the starting point of the boundary by Fourier transformation. Finally, outline feature for the nonlinear non-separable type of data was classified by using SVM. Experimental results showed the accuracy is 93.4% in average and demonstrated the feasibility of proposed system.
    Relation: Applied Mechanics and Materials 284-287, pp.3004-3009
    DOI: 10.4028/www.scientific.net/AMM.284-287.3004
    Appears in Collections:[電機工程學系暨研究所] 期刊論文
    [體育事務處] 期刊論文

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