以頭部姿勢辨識應用於家電與足型機器人之研究

簡易檢索 / 詳目顯示

回結果列表

研究生：	陳俊達 Jun-Da Chen
論文名稱：	以頭部姿勢辨識應用於家電與足型機器人之研究 Application of Head Posture Recognition Control in Home Electric Appliance and Hexapod Robot
指導教授：	鍾鴻源 Hung-Yuan Chung
口試委員:
學位類別：	碩士 Master
系所名稱：	資訊電機學院 - 電機工程學系 Department of Electrical Engineering
畢業學年度：	97
語文別：	中文
論文頁數：	108
中文關鍵詞：	殘障輔具、足型機器人、二維線性鑑別分析、主成份分析、人臉偵測、影像處理
外文關鍵詞：	Assistive Technology, Hexapod Robot, Two-dimensional Linear Discriminant Analysis, Principle Component Analysis, Face Detection, Image Processing
相關次數：	點閱：13 下載：0
分享至:	分享至facebook 分享至twitter

查詢本校圖書館目錄查詢臺灣博碩士論文知識加值系統勘誤回報

本篇論文提出以頭部轉動姿勢為控制訊號來控制家電與足型機器人的方法，主要是利用影像處理技巧來偵測出人臉所在區塊與多變量分析法中的二維線性鑑別分析法(Two-Dimensional Linear Discriminant Analysis, TDLDA)來擷取出頭部姿勢特徵，然後利用辨識出的頭部姿勢結果，如頭部正面、朝上、朝下、朝左、朝右，搭配家電控制流程機制，來控制電視的開關、音量與頻道切換，或者控制冷氣的開關、溫度的設定。以及應用頭部姿勢方向透過無線通訊模組來傳送電腦的控制命令，來控制順從式足型機器人的停止、前進、後退、左轉及右轉的動作。讓肢體障礙者可能因生病或意外傷害而失去其自由行動的能力，尤其是手部或足部功能有障礙的人士，利用本套家電自動化控制系統，可以輕鬆的控制家電使得居家生活更為便利。並且利用足型機人來模擬電動輪椅的控制，使無法行動或行動不便者也能夠利用本控制系統自由的行動。

The goal of this paper is to develop a head-pose recognition system to control the home electric appliance and a hexapod robot. The techniques of image processing and two-dimensional linear discriminant analysis are used to recognize the pose of head, such as front, up, down, left and right, to control by the process of electrical control. Then it can be used to control the switch, volume and channel of TV, or the power and temperature of AC. Otherwise it can also be used to operate the movement of a hexapod robot like stop, go forward or backward, turn left and turn right by using wireless equipments to deliver the order. For some disabled people who suffered from illness or accident, especially hands and feet injury, this system can help them to control home electric appliances easily. Besides we can invent electrical wheelchairs which are simulated by hexapod robot, combine with the system introduced in this paper. People who have trouble with moving can use this new wheelchair to move easily and conveniently.

中文摘要
英文摘要
目錄	Ⅰ
圖目錄	VI
表目錄	X
第一章  緒論	1
1 研究動機與目的	1
2 文獻回顧	2
2.1 接觸式	2
3.2 非接觸式	5
3 本論文解決方法	7
4 論文架構	8
第二章 ;軟、硬體架構介紹	9
1 軟體架構	9
1.1 人臉偵測	9
1.2 頭部姿勢參數訓練	10
1.3 頭部姿勢辨識	11
2 硬體架構	13
2.1 個人電腦	14
2.2 網路攝影機QuickCam Pro 9000	14
第三章 人臉偵測	16
1 色彩空間	16
1.1 RGB色彩空間	16
1.2 YCbCr色彩空間	18
2 膚色偵測	18
3 形態學處理	21
3.1 侵蝕	21
3.2 擴張	22
4 連接區塊標記法	24
5 直方圖等化	26
6 雙線性內插法	28
第四章 多變量統計分析	30
1 主成份分析	30
1.1 簡介	31
1.2 主成份分析在辨識上之應用	32
1.3 主成份分析在應用在辨識上的缺點	34
2  線性鑑別別分析	35
2.1 簡介	35
2.2線性鑑別別分析在辨識上之應用	36
2.3線性鑑別別分析在應用在辨識上的缺點	38
3  Fisherface	39
3.1 簡介	39
3.2 Fisherface在辨識上之應用	40
3.3 Fisherface在應用在辨識上的缺點	42
4  改良型線性鑑別別分析	42
4.1 簡介	42
4.2 改良型線性鑑別別分析在辨識上之應用	43
4.3 改良型線性鑑別別分析在應用在辨識上的缺點	45
5  非相關影像矩陣線性鑑別分析	45
5.1 簡介	45
5.2非相關影像矩陣線性鑑別分析在辨識上之應用	46
5.3非相關影像矩陣線性鑑別分析在應用在辨識上的缺點
48
6   二維線性鑑別別分析	49
6.1 簡介	49
6.2二維線性鑑別別分析在辨識上之應用	50
6.3二維線性鑑別別分析在應用在辨識上的優點	51
7  頭部姿勢參數訓練	51
8  頭部姿勢辨識	52
第五章 ;家電自動化控制	54
1  簡介	54
2   AT89S52微控制器	54
3   串列通訊傳輸	56
4   紅外線發射模組	57
第六章 ; 順從式足型機器人的設計及控制方法	58
1   順從式足型機器人介紹	58
1.1簡介	58
1.2架構規劃	59
1.3硬體結構	62
2  機器人硬體設計	64
2.1微處理器	64
2.2致動器	66
2.3編碼器	67
2.4馬達驅動功率放大電路	68
2.5繼電器煞車電路	69
2.6 RS232位準轉換電路	70
3   微處理器程式流程設計	71
4   機器人步態規劃	76
4.1對稱式三角步伐	76
4.2運動步伐規劃	77
第七章 ;實驗結果與討論	83
1  辨識率討論	83
1.1訓練與測試影像	83
1.2實驗一	84
1.3實驗二	85
2  運算時間探討	85
3家電控制實驗	86
3.1頭部姿勢定義	86
3.2家電控制流程	87
3.3家電控制介面	88
3.4家電控制分解圖	88
4  機器人移動實驗	92
4.1頭部姿勢定義	92
4.2機器人控制介面	93
4.3機器人移動分解圖	93
5  討論	98
第八章  結論與未來展望	99
1   結論	99
2  未來展望	100
參考文獻	101
附錄	105
List of Publications	108

                                

[1]J.C. Ho, “The Cursor and Robot Application via Head Posture Recognition Control,” Master Thesis, Department of Electrical Engineering, National Central University, Taiwan, 2006.
[2]C.H. Kuo, “Compliant Hexapod Robot with Web-base Remote Monitoring and Control,” Master Thesis, Department of Electrical Engineering, National Central University, Taiwan, 2004.
[3]T.Y. Chen, “The Design and Improvement of Compliant Hexapod Robot,”Master Thesis, Department of Electrical Engineering, National Central University, Taiwan, 2007.
[4]L.K. Huang, “The Development Head Control System Based on Ultrasonic,”Master Thesis, Feng Chia University, Taiwan, 2002.
[5]Y.L. Chen, “Application of tilt sensors in human-computer mouse interface for people with disabilities,”IEEE Transactions on Neural Systems and Rehabilitation Engineering., vol. 9, pp. 289-294, 2001.
[6]H. Kasper, and B.J.M Hess, “Magnetic search coil system for linear detection of three-dimensional angular movements,”IEEE Transactions on Biomedical Engineering., vol. 38, pp. 466-475, 1991.
[7]R.V. Kenyon, “A soft contact lens search coil for measuring eye mov-ements,”Vision Research., vol. 25, pp. 1629-1633, 1985.
[8]T. Imai, K. Sekine, K. Hattori, et al, “Comparing the accuracy of video-oculography and the scleral search coil system in human eye movement analysis,” Auris Nasus Larynx., vol. 32, pp. 3-9, 2005.
[9]W.J. MacLean, and R.C. Frecker, “An algebraic method for compensating for coil-placement errors in three-dimensional search-coil eye trackers,”Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 2, pp. 733-734, 1989.
[10] R. Barea, L. Boquete, M. Mazoand, and E. Lopez,“System for assisted mobility using eye movements based on electrooculography,”IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 10, no. 4, pp. 209-218, 2002.
[11]C. Chin, A.N. Barreto, J. Zhai, and C. Li, “New classification algorithm for electromyography-based computer cursor control system,”Proceeding of IEEE Southeast Con., pp. 428-432, 2005.
[12]C. N. Kuo, “Development and Application of A Multi-functional PC Camera with Eye-tracking and Head Controlled System,”Master Thesis, Feng Chia University, Taiwan., 2001.
[13] W. C. Cheng, “A Study of Powered Wheelchair Control by Using Eye-Tracking System,”Master Thesis, Feng Chia University, Taiwan, 2002.
[14] A. Kapoor, and R.W. Picard, “Real-time, fully automatic upper facial feature tracking,”IEEE International Conference on Automatic Face and Gesture Recognition., pp. 8-13, 2002.
[15]P. Ballard, and G.C. Stockman, “Computer operation via face orientation,”Proceeding of IEEE Conference on PatternRecognition., vol. 1, pp. 407- 410, 1992.
[16]J. Kim, K. R. Park, J. J. Lee, and S. R. LeClair, “Intelligent process control via gaze detection technology,” Engineering Applications of Artificial Intelligence., vol. 13, no.5, pp. 577-587, 2000.
[17] T. Morris, and V. Chauhan, “Facial feature tracking for cursor control,” Journal of Network and Computer Applications., vol. 29, no.1, pp. 62-80, 2006.
[18]Jian Yang, David Zhang, Xu Yong, Jing-yu Yang, “Two-dimensional discriminant transform for face recognition,” Pattern Recognition 38 (2005) 1125 – 1129.
[19]R. Gottumukkal, and V.K. Asari, “Real time face detection from color video stream based on PCA method,”Proceedings of the 32nd Applied Imagery Pattern Recognition Workshop, pp.146-150, 2003.
[20]R.C. Gonzalez and R.E. Woods, “Digital Image Processing Second Edition ,”Addison-Wesley Publishing, NY, 2002.
[21]連國珍，數位影像處理，台北，儒林圖書公司，民國93年，三版。
[22]林青山著，多變項分析統計法，東華書局，台北，民國79年。
[23]S.J. Lee, and S.B. Jung, “Face detection and recognition using PCA,”TENCON 99. Proceeding of the IEEE Region 10 Conference, vol.1, pp. 84-87, 1999.
[24] W.S. Lee, H.J. Lee, J.H. Chung, “Wavelet-based FLD for face recognition,” Proceedings of 43rd Circuits and Systems, vol. 2, pp.734-737, 2000.
[25]P.N. Belhumeur, J.P. Hespanha, D.J. Kriengman, “Eigenfaces vs. Fisherfaces: recognition using class specific linear projection,” IEEE Trans. Pattern Anal. Machine Intell. 19 (7) (1997) pp.711–720.
[26] Hsien-Jen Lin, “On Improving Linear Discriminant Analysis for Face Recognition with Small Sample Size Problem,” Master Thesis, National Cheng Kung University, Taiwan, 2001.
[27]J. Yang, J.-y. Yang, A.F. Frangi, D. Zhang, “Uncorrelated projection discriminant analysis and its application to face image feature extraction,” Internat. J. Pattern Recogn. Artif. Intell. 17 (8) (2003) pp.1325–1347.
[28]Altendorfer, R., Moore, N., Komsuoglu, H., Buehler, M., Brown, Jr. H. B., McMordie, D., Saranli, U., Full, R. J., and Koditschek, D. E.,“RHex-A Simple and Highly Mobile Hexapod Robot,” Autonomous Robots, vol. 11, pp. 207-220, 2001.
[29]Microchip Technology Inc,PIC18F4520 datasheet,2004.
[30]ATMEL AT89S52 Microcontroller datasheet.
[31] Texas Instruments,MAX232, MAX232 datasheet,1998.
[32]STMicroelectronics,L298N datasheet, 2000.
[33]內政部資訊科技輔具資源推廣中心http://catrp.moi.gov.tw
[34]趙春棠，PIC單晶片學習秘笈，全威，2005.
[35]施慶隆，PIC16F87X微控制器原理實習與專題應用，全華，2006.
[36]蔡朝洋、蔡承佑，單晶片微電腦80851/8951原理與應用，全華，2007.

簡易檢索 / 詳目顯示

相關論文