日常生活資訊查詢系統基於即時手勢辨識

機構典藏 > College of Engineering > Graduate Institute & Department of Computer Science and Information Engineering > Thesis > Item 987654321/74604

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/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林慧珍
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。本論文實作一個提供日常生活所需的資訊查詢系統，使用者藉由手勢來操作。利用手勢查詢資訊功能後，系統會顯示資訊和利用語音回報給使用者。在一個家庭環境中，因為家庭每位成員所需的生活資訊不同，而本論文使用了人臉辨識來區別家庭中的每位成員，進而達到個人化的服務與設定。在本論文中，我們使用主成分分析法來做人臉辨識。我們也使用主成分分析法來做手勢辨識，之後我們再用這數種手勢來操作系統。在我們的實驗中，本系統建置在家庭環境下，在少量的人臉樣本有不錯的辨識率，在手勢辨識上辨識率為93.8%，每張frame的處理速度為30到50毫秒。 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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