博碩士論文 945303010 詳細資訊




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姓名 蔡峻銘(Chun-Ming Tsai)  查詢紙本館藏   畢業系所 通訊工程學系在職專班
論文名稱 移動物偵測與追蹤之IP Camera系統
(Motion Detection and Tracking of IP Camera System)
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摘要(中) 隨著網路世界快速的發展,網路的頻寬越來越大,傳送資料的速度也越來越快,網路攝影機成為數位家庭化中的熱門產品。利用網路攝影機可以讓使用者在任何時間、任何地點觀看家中的情況。為了有效的利用網路的頻寬,必須將影像做有效的壓縮編碼,以避免當網路壅塞的時候還是可以在最短的時間內將影像資料傳送至使用者端。一般目前在IP Camera系統上最常見的壓縮編碼方式為M-JPEG與MPEG-4。而M-JPEG雖然所支援的壓縮率較低,但相對擁有硬體需求較低和價格上的優點,因此本系統選擇使用M-JPEG的IP Camera系統來進行圖片壓縮編碼,加上影像偵測與追蹤演算法追蹤特定的移動物,以應用於網路攝影機的影像追蹤上。若家中有需要照顧的老人或小孩,可以在居家中建構幾個網路攝影機,鏡頭會隨著目標物移動,改善傳統攝影機只能提供單調拍攝的缺點;對居間環境更能提供多一份的安全監控,落實以科技改善生活的理念。
摘要(英) According to the rapid development of the internet world, the network bandwidth and the transit speed have been rising up by degrees, which make the “IP-Camera” become the most popular product in digital family. The IP-Camera can make the users watch the situation at home anytime. In order to use the network bandwidth efficiently, the images must be compressed and encoded together so that they can be transited to the end-users successfully at internet obstructing time. In general, the common methodology ways in the IP Camera system are M-JPEG and MPEG-4. Although the compression rate of M-JEPG is much lower, it still has the advantages of lower hardware request and flexible price. As a result, we choose the IP Camera and its compression engine is M-JPEG to process our image processing and add the image detection and tracking algorithm to track the specific object in accordance with the application of IP-Camera. Therefore, the IP-Cameras can be set up at home to observe the elders and children who need help and improve the drawback of the monotonous shoot of tradition camera, which can offer another safe guard in family and realize the dream of making our life better by modern technology.
關鍵字(中) ★ 移動物偵測與追蹤 關鍵字(英) ★ Motion Detection and Tracking
論文目次 中文摘要 ……………………………………………………………… i
英文摘要 ……………………………………………………………… ii
目錄 ……………………………………………………………… iii
圖目錄 ……………………………………………………………… v
表目錄 ……………………………………………………………… vi
一、 序論………………………………………………………… 1
1-1 研究動機與目的…………………………………………… 1
1-2 論文架構…………………………………………………… 2
二、 基礎技術與演算法………………………………………… 3
2-1 基於輪廓基礎追蹤………………………………………… 3
2-2 基於模型的追蹤方法……………………………………… 4
2-3 基於區域的跟蹤…………………………………………… 5
2-3-1 光流法……………………………………………………… 6
2-3-2 運動能量法………………………………………………… 6
2-3-3 背景相減法………………………………………………… 7
2-4 自適應運動檢測算法及相關工作………………………… 7
2-5 靜態攝影機 , 適應性背景相減法 ……………………… 8
2-6 適應性閥值………………………………………………… 12
2-7 動態攝影機 , 位移畫面像素置換測試 ………………… 14
2-7-1 形態學濾波器……………………………………………… 15
2-7-2 形態學濾波器 – 膨脹 …………………………………… 16
2-7-3 形態學濾波器 – 侵蝕 …………………………………… 17
2-7-4 膨脹侵蝕混合遮罩………………………………………… 20
2-7-5 目標中心計算……………………………………………… 22
2-7-6 移動物偵測理論系統流程圖……………………………… 23
三、 系統架構簡介……………………………………………… 25
3-1 網際網路組成架構………………………………………… 25
3-2 網路通訊協定基本概要…………………………………… 26
3-3 TCP/IP 協定基本簡介 …………………………………… 30
3-4 TCP/IP 四層架構封包傳遞 ……………………………… 36
3-5 系統架構與規格簡介……………………………………… 40
3-5-1 系統控制流程……………………………………………… 40
3-5-2 應用程式設計流程………………………………………… 42
3-5-3 預期無法支援的狀況……………………………………… 43
四、 實驗分析與結果…………………………………………… 44
4-1 基於MATLAB進行演算法效果驗證………………………… 44
4-2 基於影像相減運算法實現於VC…………………………… 47
4-3 基於移動物偵測演算法實現於VC………………………… 49
4-4 系統架構 …………………………………………………… 50
4-5 影像增強 …………………………………………………… 51
4-6 影像偵測與追蹤 …………………………………………… 53
五、 結論與未來研究方向 ……………………………………… 57
5-1 結論 ………………………………………………………… 57
5-2 論文主要貢獻 ……………………………………………… 57
5-3 未來研究方向 ……………………………………………… 59
參考文獻 ……………………………………………………………… 61
參考文獻 [1] IEEE 802.11, http://en.wikipedia.org/wiki/802.11
[2] IEEE 802.21 D01.00, http:// www.ieee802.org/21/
[3] B.Heiselet, T Serre, M Pontil et al, “Component-based Face Detection,” Proc IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1:I657-I662, 2001.
[4] H. A. Rowley, Neural network-based human face detection, [Ph.D. thesis], Carnegie Mellon University, USA, May 1999.
[5] K. K. Sung, T. Poggio, “Example-Based Learning for View-Based Human Face Detection. Technical Report AI Memo 1521,” Massachusetts Inst. of Technology AI Lab, 1994.
[6] E. Osuna, R. Freund, and F. Girosi, “Training Support Vector Machines: An Application to Face Detection,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, 130-136, 1997.
[7] P. Viola, M. J. Jones, “Robust Real-Time Face Detection,” International Journal of Computer Vision, 57(2), 137-154, 2004.
[8] P. Viola, M. J. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features,” Computer Vision and Pattern Recognition, 1, 8-14, 2001.
[9] P. Menezes, J. C. Barreto, and J. Dias, “Face tracking based on haar-like features and eigenfaces,” in IAV2004, Lisbon, Portugal, July 2004.
[10] R. Lienhart, J. Maydt, “An Extended Set of Haar-like Features for Rapid
Object Detection,” in IEEE ICIP 2002, Vol. 1, pp 900-903, 2002.
[11] N Peterfreund, “Robust tracking of position and velocity with Kalman snakes”, attern Analysis and Machine Intelligence, IEEE Transactions on , Jun 1999, Volume 21 Issue 6, 564 - 569
[12] B. K. P. Horn, and B. G. Schunck, “Determining optical flow”, Artificial Intelligence, vol.17, pp.185-203, 1981.
[13] D. Murray, and A. Basu, “Motion Tracking with an Active Camera”, IEEE Trans. On Pattern Analysis and Machine Intelligence, Vol. 16, No. 5, pp. 449- 459, 1994.
[14] R. T. Collins, A. J. Lipton, T. Kanade, H. Fujiyoshi, D. Duggins, Y. Tsin, D. Tolliver, N. Enomoto, O. Hasegawa, P. Burt, and L. Wixson, “A system for surveillance and monitoring”, The Robotics Institute, Carnegie Mellon University, Pittsburgh PA, Tech. Rep. CMU-RI-TR-00-12, 2000.
[15] C. Ridder, O. Munkelt, and H. Kirchner. “Adaptive Background Estimation and Foreground Detection using Kalman-Filtering”, Proceedings of International Conference on recent Advances in Mechatronics, ICRAM
[16] M. Allman, et al, “TCP Congestion Control”, RFC 2581, Internet Engineering Task Force, April 1999
[17] Jeremy Bentham, “TCP/IP LEAN Web Servers for Embedded Systems 2/e”, 2002
[18] W. Richard Stevens, “TCP/IP Illustrated Volumn1, Volumn2, 2000
[19] DOUGLAS E.COMER 原著, 張智勝.陳伯偉編譯, TCP/IP互連網路, 全華科技圖書股份有限公司, 2001年七月.
[20] 蕭文龍、林松儒編著, TCP/IP最佳入門實用書, □峰資訊股份有限公司
[21] 楊豐瑞、楊豐任編著, 網路概論與實務, 松崗電腦圖書資料股份有限公司, 2001年1月
[22] Rehg, J.M., Kanade, T., “Model-based tracking of self-occluding articulated objects”, Computer Vision, 1995. Proceedings., Fifth International Conference on, 20-23 Jun 1995, 612 - 617
[23] C. Kim, and J. N. Hwang, “Fast and automatic video object segmentation and track for content-based applications”, IEEE Transactions Circuits and System for Video Technology, vol.12, pp.122-129, Feb. 2002.
[24] D. Comaniciu, V. Ramesh, and P. Meer , “Kernel-based object tracking”, Real-Time Vision & Modeling Dept., Siemens Corporate Res., Princeton, NJ, USA.
[25] D. S. Jang, and H.-I. Choi, “Active models for tracking moving objects”, Pattern Recognit, vol. 33, no. 7, pp. 1135–1146, 2000.
[26] R. E. Kalman, “A new approach to linear filtering and prediction problems”, Transactions of the ASME - Journal of Basic Engineering Vol. 82: pp. 35-45 (1960).
[27] C. R. Wren, A. Azarbayejani, T. Darrell, and A. P. Pentland, “Pfinder: real-time tracking of the human body”, IEEE Trans. Pattern Anal. Machine Intell., vol. 19, pp.780–785, July 1997.
[28] S. McKenna, S. Jabri, Z. Duric, A. Rosenfeld, and H. Wechsler, “Tracking groups of people”, Comput. Vis. Image Understanding, vol. 80, no. 1, pp. 42–56, 2000.
[29] 繆紹剛,"數位影像處理-活用MATLAB",全華圖書 2005。
[30] 鐘國亮,"影像處理與電腦視覺",東華書局,2006。
[31] http://zh.wikipedia.org/wiki/TCP/IP
[32] http://khchu.tripod.com/doc/tcpip/tcpip.htm
指導教授 吳中實(Jung-Shyr Wu) 審核日期 2011-7-25
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