Responsive image
博碩士論文 etd-0717109-174103 詳細資訊
Title page for etd-0717109-174103
論文名稱
Title
應用平均位移法於變形物體之即時視覺追循
Application of Mean Shift to Real-Time Visual Tracking for a Deformable Object
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
70
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2009-07-03
繳交日期
Date of Submission
2009-07-17
關鍵字
Keywords
平均位移法、變形物體、即時、視覺伺服
deformed object, visual servo, mean shift, real-time
統計
Statistics
本論文已被瀏覽 5679 次,被下載 2806
The thesis/dissertation has been browsed 5679 times, has been downloaded 2806 times.
中文摘要
本文為追尋一可變形物體並保持攝影機朝向該目標物,藉由改善以往的伺服視覺架構建立了一套包含二維迴轉機台及CCD攝影機維的高強健性主動式即時追尋系統。在影像處理上藉由平均位移理論建立一高效率的樣本比對及搜尋機制,並加入核心函數、背景權重與樣本更新機制加強系統之強健性,令系統在目標物體外型上有所變化時依然可以成功追尋。將數位影像上所得之資訊回授予二維迴轉機台及卡爾曼濾波器,使機台朝向目標轉動,將目標物維持在攝影機視野中央。
由實驗的結果可以知道,本系統在追蹤物體有模糊、遮蔽、變形、相似物體交錯運動等情形下皆可以順利運作,且效率達一般攝影機所能擷取影像之速度(30 fps)的兩倍以上。
Abstract
This thesis presents a robust real-time active tracking system with a pan-tilt camera. The proposed visual servo framework is able to track a deformed object and maintain the target always inside the field of view. For the image processing, an efficient template matching and searching method using the mean-shift theory is developed. The robustness is achieved by appending the ratio histogram, a kernel function, and the template update to the framework when the target is deformed. Then the pan-tilt unit turns towards the target and keeps the target inside the field of view of the camera by feeding back the position information to a Kalman filter.
Experimental results show that the presented scheme works successfully when the target is vague or concealed or deformed. The visual tracking task can also be accomplished even when a similar object crosses over the target. In addition, the refreshing rate can be up to 60 frames per second.
目次 Table of Contents
目錄 I
圖表目錄 III
摘要 V
Abstract VI
第一章 緒論 1
1.1 研究背景與目的 1
1.2 文獻回顧 2
1.3 本文架構 4
第二章 影像處理 5
2.1 色彩空間 5
2.1.1 RGB與灰階 5
2.1.2 HSV色彩空間 6
2.2 樣本匹配 7
2.2.1 核心函數 8
2.2.2 機率密度函數 10
2.2.3 相似度函數 12
2.2.4 背景權重 15
第三章 目標搜尋 18
3.1 搜尋法簡介 18
3.2 平均位移法 23
3.3 目標尺寸估計 27
3.3.1 權重法 28
3.3.2 尺度空間法(Scale Space) 28
3.3.3 連續適應性平均位移法(CAM-Shift) 30
第四章 實驗與分析 33
4.1 實驗設備 33
4.1.1 攝影機模型 34
4.1.2 Pan-Tilt機台模型 37
4.1.3 卡爾曼濾波器(Kalman filter) 42
4.2 實驗與驗證 45
4.2.1 固定背景追尋 46
4.2.2 動態影像追尋 50
4.2.3 追尋中目標物與相似物體交錯 51
4.2.4 卡爾曼濾波器於機台控制之主動追尋 52
第五章 結論與建議 56
參考文獻 58
參考文獻 References
[1] J. Hill and W. T. Park, “Real Time Control of a Robot With a Mobile Camera,” in Proc. 9th ISIR, Washiington, D.C.: 1979, pp. 233-246.
[2] Wenmiao Lu and Yap-Peng Tan, “A Color Histogram Based People Tracking System,” Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International Symposium on, 2001, pp. 137-140 vol. 2.
[3] C. Harris and M. Stephens, “A Combined Corner and Edge Detection,” Proceedings of The Fourth Alvey Vision Conference, 1988, pp. 151, 147.
[4] Y. Jung, K. Lee, and Y. Ho, “Feature-Based Object Tracking with an Active Camera,” Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing, Springer-Verlag, 2002, pp. 1137-1144.
[5] I. Sobel, “Neighborhood Coding of Binary Images for Fast Contour Following and General Binary Array Processing,” Computer Graphics and Image Processing, vol. 8, 1978, pp. 127-138.
[6] M. Kass, A. Witkin, and D. Terzopoulos, “Snake: Active Contour Models,” International Journal of Computer Vision, 1987, pp. 321-331.
[7] O. Faugeras and R. Keriven, “Variational Principles, Surface Evolution, PDEs,Level Set Methods, and The Stereo Problem,” Image Processing, IEEE Transactions on, vol. 7, 1998, pp. 336-344.
[8] A.Y. Xin, X. Li, and M. Shah, “Object Contour Tracking Using Level Sets,” ASIAN CONFERENCE ON COMPUTER VISION, ACCV 2004, JAJU ISLANDS, KOREA, 2004.
[9] J.G. Allen, R.Y.D. Xu, and J.S. Jin, “Object tracking using CamShift algorithm and multiple quantized feature spaces,” Proceedings of the Pan-Sydney area workshop on Visual information processing, Australian Computer Society, Inc., 2004, pp. 3-7.
[10] Reoxiang Li, Bing Zeng, and M. Liou, “A New Three-Step Search Algorithm for Block Motion Estimation,” Circuits and Systems for Video Technology, IEEE Transactions on, vol. 4, 1994, pp. 438-442.
[11] T. Cacoullos, “Estimation of A Multivariate Density,” Annals of the Institute of Statistical Mathematics, vol. 18, Dec. 1966, pp. 179-189.
[12] D. Comaniciu and P. Meer, “Mean shift: A Robust Approach Toward Feature Space Analysis,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 24, 2002, pp. 603-619.
[13] J. Allen, R. Xu, and J. Jin, “Mean Shift Object Tracking for A SIMD Computer,” Information Technology and Applications, 2005. ICITA 2005. Third International Conference on, 2005, pp. 692-697 vol.1.
[14] Diaconis P., “Sequential Monte Carlo Methods in Practice,” Journal of the American Statistical Association, vol. 98, 2003, pp. 496-497.
[15] S. Mantri and D. Bullock, “A neural network based vehicle detection and tracking system,” Proceedings of the 27th Southeastern Symposium on System Theory (SSST'95), IEEE Computer Society, 1995, p. 279.
[16] Xuguang Zhang, Honghai Sun, and Yanjie Wang, “Integrated Intensity, Orientation Code and Spatial Information for Robust Tracking,” Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on, 2007, pp. 1842-1846.
[17] ITU-R Rec. BT.601-4, “Encoding Parameters of Digital Television for Studios,” Jul. 1994.
[18] G. Bradski, “Computer Vision Face Tracking For Use in a Perceptual User Interface,” Intel Technology Journal, 2nd Quarter. 1998.
[19] J.G. Allen, R.Y.D. Xu, and J.S. Jin, “Object Tracking Using CamShift Algorithm and Multiple Quantized Feature Spaces,” Proceedings of the Pan-Sydney area workshop on Visual information processing, Australian Computer Society, Inc., 2004, pp. 3-7.
[20] D. Comaniciu, V. Ramesh, and P. Meer, “Kernel-Based Object Tracking,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, 2003, pp. 564-575.
[21] A. Bhattacharyya, “On a Measure of Divergence Between Two Statistical Populations Defined by Probability Distributions,” Bull. Calcutta Math. Soc., 1943, pp. 99-109.
[22] M.J. Swain and D.H. Ballard, “Color Indexing,” International Journal of Computer Vision, vol. 7, Nov. 1991, pp. 11-32.
[23] D. Comaniciu, V. Ramesh, and P. Meer, “Real-time Tracking of Non-rigid Objects Using Mean Shift,” Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on, 2000, pp. 142-149.
[24] T. Lindeberg, “Feature Detection with Automatic Scale Selection,” Int. J. Comput. Vision, vol. 30, 1998, pp. 79-116.
[25] R. Collins, “Mean-shift Blob Tracking Through Scale Space,” Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on, 2003, pp. II-234-40 vol.2.
[26] B.K.P. Horn, Robot Vision, The MIT Press, 1986.
[27] R. Kalman, “A New Approach to Linear Filtering and Prediction Problems,” Transactions of the ASME – Journal of Basic Engineering, 1960, pp. 35-45.
[28] R.E. Kalman and R.S. Bucy, “New Results in Linear Filtering and Prediction Theory,” Transactions of the ASME - Journal of Basic Engineering, vol. 83, 1961, pp. 95-107.
[29]周政德,“應用更新樣本於變形物體之視覺伺服”, 國立中山大學機械與機電研究所碩士論文,民國九十七年七月。
電子全文 Fulltext
本電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
論文使用權限 Thesis access permission:校內立即公開,校外一年後公開 off campus withheld
開放時間 Available:
校內 Campus: 已公開 available
校外 Off-campus: 已公開 available


紙本論文 Printed copies
紙本論文的公開資訊在102學年度以後相對較為完整。如果需要查詢101學年度以前的紙本論文公開資訊,請聯繫圖資處紙本論文服務櫃台。如有不便之處敬請見諒。
開放時間 available 已公開 available

QR Code