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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 傅立成 | |
dc.contributor.author | Chih-Hung Lin | en |
dc.contributor.author | 林志鴻 | zh_TW |
dc.date.accessioned | 2021-06-15T02:44:16Z | - |
dc.date.available | 2012-01-21 | |
dc.date.copyright | 2010-01-21 | |
dc.date.issued | 2009 | |
dc.date.submitted | 2009-08-10 | |
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Corradini, 'Dynamic time warping for off-line recognition of a small gesture vocabulary,' IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, pp. 82-89, 2001. [18] L. Hong and M. Greenspan, 'Multi-scale gesture recognition from time-varying contours,' IEEE International Conference on Computer Vision, pp. 236-243 Vol. 1, 2005. [19] E. W. Huang and L. C. Fu, 'Gesture Stroke Recognition Using Computer Vision and Linear Accelerometer,' Automatic Face and Gesture Recognition, IEEE International on, 2008. [20] C.-H. Lin, E.-W. Huang, and L.-C. Fu, 'Fast Accelerometer-Based Continuous Gesture Recognition Using Kernel-Based Matching Method,' International Conference on Human-Computer Interaction: Springer, 2009. [21] S. P. Smith and A. K. Jain, 'A test to determine the multivariate normality of a data set,' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, pp. 757-761, 1988. [22] W. Day and H. 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Li, 'Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes,' ACM symposium on User interface software and technology Newport, Rhode Island, USA: ACM, 2007. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44193 | - |
dc.description.abstract | Human gesture is commonly used in daily communication between humans, and there are more and more studies trying to utilize gestures in human computer interaction. Because the advance of wireless and accelerometer technologies, accelerometer which is constrained by the environment compared with other sensing devices is getting more and more interested in these studies. In this thesis, we introduce an accelerometer-based gesture recognition system which is composed of gesture characteristic database and continuous gesture recognition. In the gesture characteristic database, we propose a method to construct a gesture characteristic database which can handle intra-class variations of human hand gestures. In the continuous gesture recognition part, a kernel based matching method and a dynamic time warping based method are proposed to recognize gestures in human hand motions. We here design two different gesture sets in the experiments, and the experiment results show that our system can recognize continuous hand gestures quickly and accurately. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T02:44:16Z (GMT). No. of bitstreams: 1 ntu-98-R95922072-1.pdf: 564406 bytes, checksum: e6e90e6e6d888191adaa73517520fae1 (MD5) Previous issue date: 2009 | en |
dc.description.tableofcontents | 口試委員審定書 #
誌謝 i 中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vi LIST OF TABLES viii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Problem Description 3 1.3 System Overview 5 1.4 Organization 8 1.5 Related Works 8 1.5.1 Gesture Model Construction 9 1.5.2 Gesture Spotting 10 1.5.3 Gesture Classification 11 Chapter 2 Preliminary 13 2.1 Polar Coordinate System 13 2.2 Multivariate Gaussian Distribution 15 2.3 Agglomerative Hierarchical Clustering 16 2.4 Pyramid Matching Kernel 18 2.5 Dynamic Time Warping 21 Chapter 3 Gesture Characteristic Database 25 3.1 Overview 25 3.2 Feature Extraction 26 3.2.1 Signal Preprocessing 26 3.2.2 Acceleration Trajectory in Cartesian Coordinate System 28 3.2.3 Acceleration Trajectory in Polar Coordinate System 29 3.3 Gesture Characteristic Modeling 30 Chapter 4 Continuous Gesture Recognition 35 4.1 Overview 35 4.2 Gesture Spotting 36 4.2.1 Motion Detection 36 4.2.2 Candidate Searching 38 4.3 Gesture Classification 43 4.4 Continuous Gesture Recognition Algorithm 47 Chapter 5 Experiment 49 5.1 Environment Description 49 5.2 Gesture Sample Collection 50 5.3 Gesture Characteristic Training 51 5.4 Experiment Result 52 5.4.1 Performance of isolated gesture Recognition 53 5.4.2 Performance of continuous gesture Recognition 55 Chapter 6 Conclusion 57 REFERENCE 59 | |
dc.language.iso | en | |
dc.title | 應用在人機互動中基於加速度感測器之連續手勢辨識 | zh_TW |
dc.title | Accelerometer-Based Continuous Gesture Recognition For Human Computer Interaction | en |
dc.type | Thesis | |
dc.date.schoolyear | 97-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 歐陽明,洪一平,蘇木春,李蔡彥 | |
dc.subject.keyword | 人機互動,加速度感測器,手勢辨識, | zh_TW |
dc.subject.keyword | HCI,Accelerometer,Gesture Recognition, | en |
dc.relation.page | 61 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2009-08-10 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
顯示於系所單位: | 資訊工程學系 |
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ntu-98-1.pdf 目前未授權公開取用 | 551.18 kB | Adobe PDF |
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