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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/74604

    Title: 日常生活資訊查詢系統基於即時手勢辨識
    Other Titles: A real-time hand gesture recognition system for daily information retrieval from internet
    Authors: 彭聖喻;Peng, Sheng-Yu
    Contributors: 淡江大學資訊工程學系碩士班
    Keywords: 人臉辨識;手勢辨識;主成分分析;face recognition;Hand gesture recognition;Principal component analysis
    Date: 2011
    Issue Date: 2011-12-28 19:01:31 (UTC+8)
    Abstract: 現今日常生活中,人們經常習慣從網路取得日常生活中的資訊,例如:天氣、新聞、運勢等等資訊,而這些資訊卻要每天重複操作著一樣的滑鼠、鍵盤動作來取得,日月累積下來浪費了不少時間,本研究將這些資訊整合做成一個系統,透過手勢辨識的方式,讓使用者方便地取得資訊,提供給使用者另一種取得這些資訊的方式。
    Nowadays people are used to get daily information from Internet such as weather condition, news and financial information, among others. Though, in order to receiving these daily information, users have to repeat same mouse and keyboard actions, inducing waste of time and inconvenience. In order to improve these situations, we propose in this paper a system design that can easily get daily information without mouse and keyboard actions and make people''s life more convenient and easier. In this proposed system, we have implemented an approach that provides daily information retrieved from Internet, where users can operate this system with his hands’ movements. Once selected the function by hand gestures, the system will report action information to users by synthetized speech. In a typical family, since each member has different requirements and needs, the system utilizes face recognition to identify each user, bringing up personalized services to each user.
    In this paper, we use principal component analysis method to recognize faces as also hand gestures, and then a number of hand gestures and system controls are acquired and stored into this system. Results from a set of experiments indicate that the proposed system in a family environment with small-scale of face recognition show good performance as also good result in hand gesture recognition.
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

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