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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/68807

    Title: 即時手勢辨識系統及其於戰場情資顯示平台之應用;A Real-Time Hand Gesture Recognition System and its Application in a Battlefield Information Platform
    Authors: 羅冠中;Lo,Kuan-zhong
    Contributors: 資訊工程學系
    Keywords: 深度攝影機;人機互動;手勢辨識
    Date: 2015-07-28
    Issue Date: 2015-09-23 14:30:27 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 近年來,手勢辨識在人機互動的相關研究中,吸引了各個領域的專家投入,而常見的應用有遊戲控制、機械手臂操作、機器人控制及家電控制等等。其簡單又直覺的操作方式,將漸漸地取代傳統遙控器和輸入裝置的使用。
    本論文提出一種基於深度影像之即時手勢辨識系統,並將系統應用於以NASA world wind為基礎之戰場環境情資平臺的操控。我們所開發的以NASA world wind為基礎之戰場環境情資平臺,除了可顯示最基本的世界地圖資訊之外,它也提供了許多地理與環境資訊,可以滿足國軍基層部隊的需求。
    ;For the past few years, gesture recognition research in human-computer interaction had attracted experts’ attention in various field, general applications includes gaming control, humanoid robot arms operation, robot control, household appliances control and so on. Due to its convenience and intuitive manipulation, the hand-gesture-based controller will gradually substitute for the traditional remote and input device control.
    This thesis presents a real-time hand gesture recognition system based on depth image, and apply the system to the battlefield information platform which based on NASA world wind. The NASA world wind-based battlefield information platform not only displays the information of the world maps but offers a number of geographical and environmental information that satisfy the demands of military.
    The implementation of the proposed hand gesture recognition system is as follows. First of all, we locate the arm region from an image captured by Kinect via several necessary depth image preprocessing operators and skeleton tracking operators. Second, use a hand capture algorithm to extract the hand shape from the arm region. We then use the distance curve between hand boundary and the hand center as a feature that describing hand shape. However it’s inappropriate to be used for the hand shape recognition directly since the feature still affected by angle for hand rotation and size of hand. Thus, we use the frequency domain coefficient of the distance curve transformed by Fast Fourier transform. On account that there are different hand shape resulting different Fast Fourier coefficient, the decision tree incorporated with the coefficient is adopted to recognition 6 gestures. Furthermore, arranging those gesture with both hands will be used as commands to control the battlefield information platform.
    The NASA world wind-based battlefield information platform not only displays the information of the world maps but offers a number of geographical and environmental information that satisfy the demands of military. The aim of this system is to provide a brand-new battlefield platform for the military. In addition to operating by traditional keyboard and mouse, this system also introduce the latest technology of human-computer interaction. After all, several experiments were designed to evaluate the functionalities of the proposed real-time hand gesture recognition system. In hand gesture experiments, the correct rate is 97.1%. Even at different angles, the correct rate in the commands experiment with both hand is 97.42%.
    Appears in Collections:[Graduate Institute of Computer Science and Information Engineering] Electronic Thesis & Dissertation

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