請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/51086
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳中平(Chung-Ping Chen) | |
dc.contributor.author | Chih Chang | en |
dc.contributor.author | 張智 | zh_TW |
dc.date.accessioned | 2021-06-15T13:24:57Z | - |
dc.date.available | 2019-07-06 | |
dc.date.copyright | 2016-07-06 | |
dc.date.issued | 2016 | |
dc.date.submitted | 2016-06-07 | |
dc.identifier.citation | [1] Silanon, Kittasil, and Nikom Suvonvorn. 'Fingertips Tracking Based Active Contour for General HCI Application.' Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013). Springer Singapore, 2014.
[2] Dhawan, Amiraj, and Vipul Honrao. 'Implementation of Hand Detection based Techniques for Human Computer Interaction.' arXiv preprint arXiv:1312.7560(2013). [3] Yeo, Hui-Shyong, Byung-Gook Lee, and Hyotaek Lim. 'Hand tracking and gesture recognition system for human-computer interaction using low-cost hardware.' Multimedia Tools and Applications 74.8 (2013): 2687-2715. [4] Li, Yi. 'Hand gesture recognition using Kinect.' Software Engineering and Service Science (ICSESS), 2012 IEEE 3rd International Conference on. IEEE, 2012. [5] Trapero Cerezo, F. '3D Hand and Finger Recognition using Kinect.' University of Granada (UGR), Spain (2012). [6] ZHENG, Mei-sheng, Ning CHEN, and Chao SONG. 'An algorithm for determining the largest internal circle in arbitrary polygons.' Machinery Design & Manufacture 5 (2003): 036. [7] Hasan, Haitham, and S. Abdul-Kareem. 'Static hand gesture recognition using neural networks.' Artificial Intelligence Review 41.2 (2014): 147-181. [8] Bouchrika, Tahani, et al. 'Neural solutions to interact with computers by hand gesture recognition.' Multimedia Tools and Applications 72.3 (2014): 2949-2975. [9] Lockton, Ray. 'Hand gesture recognition using computer vision.' 4th Year Project Report (2002): 1-69. [10] Biswas, Kanad K., and Saurav Kumar Basu. 'Gesture recognition using Microsoft Kinect®.' Automation, Robotics and Applications (ICARA), 2011 5th International Conference on. IEEE, 2011. [11] Ren, Zhou, et al. 'Robust hand gesture recognition with kinect sensor.'Proceedings of the 19th ACM international conference on Multimedia. ACM, 2011. [12] Dominio, Fabio, Mauro Donadeo, and Pietro Zanuttigh. 'Combining multiple depth-based descriptors for hand gesture recognition.' Pattern Recognition Letters 50 (2014): 101-111. [13] Kurakin, Alexey, Zhengyou Zhang, and Zicheng Liu. 'A real time system for dynamic hand gesture recognition with a depth sensor.' Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. IEEE, 2012. [14] Yao, Yuan, and Yun Fu. 'Contour model-based hand-gesture recognition using the Kinect sensor.' Circuits and Systems for Video Technology, IEEE Transactions on 24.11 (2014): 1935-1944. [15] Qian, Chen, et al. 'Realtime and robust hand tracking from depth.' Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014. [16] Ren, Zhou, Junsong Yuan, and Zhengyou Zhang. 'Robust hand gesture recognition based on finger-earth mover's distance with a commodity depth camera.' Proceedings of the 19th ACM international conference on Multimedia. ACM, 2011. [17] Ren, Zhou, et al. 'Robust part-based hand gesture recognition using kinect sensor.' Multimedia, IEEE Transactions on 15.5 (2013): 1110-1120. [18] Sharp, Toby, et al. 'Accurate, Robust, and Flexible Real-time Hand Tracking.'Proc. CHI. Vol. 8. 2015. [19] Chen, Zhi-hua, et al. 'Real-Time Hand Gesture Recognition Using Finger Segmentation.' The Scientific World Journal 2014 (2014). [20] Du, Heng, and TszHang To. 'Hand gesture recognition using Kinect.' Techical Report, Boston University (2011). [21] Oikonomidis, Iason, Nikolaos Kyriazis, and Antonis A. Argyros. 'Efficient model-based 3D tracking of hand articulations using Kinect.' BMVC. Vol. 1. No. 2. 2011. [22] Raheja, Jagdish L., Ankit Chaudhary, and Kunal Singal. 'Tracking of fingertips and centers of palm using kinect.' Computational intelligence, modelling and simulation (CIMSiM), 2011 third international conference on. IEEE, 2011. [23] Premaratne, Prashan, Sabooh Ajaz, and Malin Premaratne. 'Hand gesture tracking and recognition system using Lucas–Kanade algorithms for control of consumer electronics.' Neurocomputing 116 (2013): 242-249. [24] Hernández-Vela, Antonio, et al. 'Probability-based dynamic time warping and bag-of-visual-and-depth-words for human gesture recognition in rgb-d.' Pattern Recognition Letters 50 (2014): 112-121. [25] Elgendi, Mohamed, Flavien Picon, and N. Magenant-Thalmann. 'Real-time speed detection of hand gesture using, Kinect.' Proc. Workshop on Autonomous Social Robots and Virtual Humans, The 25th Annual Conference on Computer Animation and Social Agents (CASA 2012). 2012. [26] Liu, Kui, et al. 'Fusion of inertial and depth sensor data for robust hand gesture recognition.' Sensors Journal, IEEE 14.6 (2014): 1898-1903. [27] Wang, Youwen, et al. 'Kinect based dynamic hand gesture recognition algorithm research.' Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2012 4th International Conference on. Vol. 1. IEEE, 2012. [28] Bhuyan, M. K., et al. 'A novel set of features for continuous hand gesture recognition.' Journal on Multimodal User Interfaces 8.4 (2014): 333-343. [29] Ju, Zhaojie, et al. 'Depth and RGB image alignment for hand gesture segmentation using Kinect.' Machine Learning and Cybernetics (ICMLC), 2013 International Conference on. Vol. 2. IEEE, 2013. [30] Hasan, Haitham, and S. Abdul-Kareem. 'Static hand gesture recognition using neural networks.' Artificial Intelligence Review 41.2 (2014): 147-181. [31] Bouchrika, Tahani, et al. 'Neural solutions to interact with computers by hand gesture recognition.' Multimedia Tools and Applications 72.3 (2014): 2949-2975. [32] Hasan, Haitham, and Sameem Abdul-Kareem. 'Human–computer interaction using vision-based hand gesture recognition systems: a survey.' Neural Computing and Applications 25.2 (2014): 251-261. [33] Chaudhary, Ankit, et al. 'Intelligent approaches to interact with machines using hand gesture recognition in natural way: a survey.' arXiv preprint arXiv:1303.2292 (2013). [34] Rautaray, Siddharth S., and Anupam Agrawal. 'Vision based hand gesture recognition for human computer interaction: a survey.' Artificial Intelligence Review 43.1 (2015): 1-54. [35] Qian, Kun, Jie Niu, and Hong Yang. 'Developing a gesture based remote human-robot interaction system using kinect.' International Journal of Smart Home 7.4 (2013). [36] Ohn-Bar, Eshed, and Mohan Manubhai Trivedi. 'Hand gesture recognition in real time for automotive interfaces: A multimodal vision-based approach and evaluations.' Intelligent Transportation Systems, IEEE Transactions on 15.6 (2014): 2368-2377. [37] Karam, Maria. PhD Thesis: ' A framework for research and design of gesture-based human-computer interactions. ' Diss. University of Southampton, 2006. [38] Sklansky, Jack. 'Measuring concavity on a rectangular mosaic.' IEEE Transactions on Computers 21.12 (1972): 1355-1364. [39] Bykat, Alex. 'Convex hull of a finite set of points in two dimensions.' Information Processing Letters 7.6 (1978): 296-298. [40] McCallum, Duncan, and David Avis. 'A linear algorithm for finding the convex hull of a simple polygon.' Information Processing Letters 9.5 (1979): 201-206. [41] Melkman, Avraham A. 'On-line construction of the convex hull of a simple polyline.' Information Processing Letters 25.1 (1987): 11-12. [42] Manresa, Cristina, et al. 'Hand Tracking and Gesture Recognition for Human-Computer Interaction.' Electronic Letters on Computer Vision and Image Analysis 5.3 (2005): 96-104. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/51086 | - |
dc.description.abstract | 人機互動領域中,指尖追蹤技術扮演著相當重要的角色,因為此技術可同時應用於手勢辨識及手部動作的偵測,且被廣泛應用於虛擬實境、手語辨識和智慧型裝置,這也使指尖追蹤技術成為近年的熱門研究主題。縱然先前已有許多手勢辨識相關之研究,但傳統以視覺為基礎的手勢辨識方法距滿足現今生活需要仍有一段距離。
在此論文中,將講述一個使用Microsoft Kinect for Xbox One來進行指尖追蹤技術的方法,且使用Microsoft Visual Studio 2013來實行此即時指尖追蹤系統。此系統將能偵測到使用者的手,並辨別手指,進而顯示各個指尖的相對座標與深度座標於螢幕上。此即時指尖追蹤系統的準確度約為 97.1%.。 由於Kinect所使用的深度感測器為紅外線照相機,所以此系統的表現將受到光線及背景等因素所造成的些微影響。此系統的準確度及完善度使之成為一個在日常生活中,能被整合成各種不同應用的多功能的要素。 | zh_TW |
dc.description.abstract | Fingertips tracking is of great importance for human-computer interaction (HCI), because it can be applied both in the hand gesture recognition (HGR) and hand movement detection. And its extensive applications in virtual reality, sign language recognition, and smart device makes it a hot research topic in recent years. Despite lots of previous work, traditional vision-based hand gesture recognition methods are still far from satisfactory for real-life applications.
In this thesis, a novel method for fingertips tracking using the Microsoft Kinect for Xbox One is described, and a real-time fingertips tracking system is implemented with Microsoft Visual Studio 2013. The system is able to detect the hand of the user, to identify fingers, and to display the relative axis and depth axis information of fingertips on screen. The overall accuracy of the real-time fingertips tracking system is about 97.1%. Because the depth sensor of the Kinect is an infrared camera, the lighting conditions and background have little impact on the performance of this system. The accuracy and robustness make this system a versatile component that can be integrated in a variety of applications in daily life. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T13:24:57Z (GMT). No. of bitstreams: 1 ntu-105-R02945035-1.pdf: 3377721 bytes, checksum: e3b37a007ee3679dadd14b84f6e7ca69 (MD5) Previous issue date: 2016 | en |
dc.description.tableofcontents | 口試委員會審定書 #
誌謝 i 中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vi LIST OF TABLES vii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Hand Gesture Recognition 3 1.3 Proposed Approach 4 1.4 Thesis Overview 6 Chapter 2 Hand Gesture Recognition 8 2.1 Sensor and System 8 2.2 Body Tracking 13 2.3 Build-in Hand State Recognition 17 2.4 Previous Hand Gesture Recognition Approaches 19 Chapter 3 Hand Part Extraction 26 3.1 Hand Tracking 27 3.2 Hand Part Segmentation 28 Chapter 4 Hand Information Collection 31 4.1 Hand Contour 31 4.2 Convex-Hull and Outer Points 37 4.3 Inner Points 42 4.4 Maximum Inscribed Circle 43 4.4.1 Brute Force Method 43 4.4.2 Distance Transform Method 44 4.4.3 The Polygon Method 47 4.4.4 Results 49 Chapter 5 Finger Identification 51 5.1 Convexity Defects 52 5.2 Finger Points 55 5.3 Exact Fingertips 59 Chapter 6 Results and Conclusions 60 6.1 Results 60 6.2 Conclusions 69 REFERENCE 71 | |
dc.language.iso | en | |
dc.title | 基於Kinect之三維即時指尖追蹤演算法 | zh_TW |
dc.title | Real-time Three-dimensional Fingertips Tracking Algorithm Based on the Kinect Sensor | en |
dc.type | Thesis | |
dc.date.schoolyear | 104-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 傅立成(Li-Chen Fu),傅楸善(Chiou-Shann Fuh),賴飛羆(Fei-Pei Lai) | |
dc.subject.keyword | 人機互動,手勢辨識,指尖追蹤,電腦視覺,模式識別,影像處理,手語辨識,Kinect, | zh_TW |
dc.subject.keyword | Human Computer Interaction (HCI),Hand Gesture Recognition (HGR),Fingertips Tracking,Computer Vision,Pattern Recognition,Image Processing,Sign language Gesture recognition,Kinect, | en |
dc.relation.page | 75 | |
dc.identifier.doi | 10.6342/NTU201600281 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2016-06-07 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電子工程學研究所 | zh_TW |
顯示於系所單位: | 電子工程學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-105-1.pdf 目前未授權公開取用 | 3.3 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。