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論文中文名稱:多攝影機協同視訊監控系統 [以論文名稱查詢館藏系統]
論文英文名稱:A Cooperative Video Surveillance System by Using Multiple Cameras [以論文名稱查詢館藏系統]
英文姓名:Ti-Hua Yang
英文關鍵詞:Video SurveillanceMulti-Camera CooperativeGraph Topology with Spatial RelationshipObject Detection and TrackingAbnormal Event Detection
論文英文摘要:The third generation surveillance system had become trends in the surveillance industry after the 911 in 2001. The key concept of it is the fully digitization of the surveillance system. However, it is still using the traditional manner to observe the output by human. Since the spatial relationship between the multi-cameras has not been defined, there will be a defect that the security officer can only watch the individual scene of each camera, but not the overall view for whole monitoring area. Furthermore, once the distribution of the multi-cameras are changed, the work complexity of the surveillance system will increase.
Therefore, the purpose of our research is to design a multi-cameras cooperative video surveillance system which can improve the defects mentioned above. We propose a novel model building a graph topology with spatial relationship into our surveillance system, which improves the performance while detecting and tracking an object; controls multi-cameras by one central station; alerts the inspectors for the abnormal events immediately and effectively.
After a series of experiments, we can show that the graph topology with spatial relationship in the surveillance system is not only more adaptive for the indoor space but also more flexible for the detection region. Our design provides a basic architecture for multi-points surveillance system in the future.
摘要 I
致謝 III
目錄 IV
表目錄 VII
圖目錄 VIII
第1章 緒論 1
1.1 研究動機 1
1.2 研究目的 3
1.3 研究範圍與限制 3
1.4 論文架構 4
第2章 相關技術與文獻討論 6
2.1 建構圖形拓撲 6
2.2 背景更新 8
2.3 物件分割 9
2.4 物件追蹤 10
2.5 異常變動偵測 13
2.6 多攝影機監控系統 14
第3章 系統架構 15
3.1 監控系統架構 15
3.2 監控系統運作流程 16
第4章 初始化流程 18
4.1 建立具有空間涵蓋完整性之多攝影機監控區域 18
4.2 根據指定空間建立空間關係圖形拓撲 19
4.3 空間關係圖形拓撲之資料結構 20
4.4 設定條件路徑以及警戒、偵測、離開區域 21
第5章 多攝影機變動偵測 24
5.1 背景學習與更新 25
5.2 變動偵測 26
第6章 物件分割與特徵擷取 28
6.1 背景相減法 28
6.2 目標物體特徵擷取 30
6.2.1 擷取膚色特徵方法 30
6.2.2 擷取色彩直方圖方法 31
第7章 圖形拓撲追蹤物件 34
7.1 圖形拓撲追蹤物件方法 35
7.2 異常事件偵測 38
7.3 判斷目標物體是否已離開監控範圍 40
第8章 歷史資料查詢 41
8.1 資料庫設計 41
8.2 資料查詢方式 48
第9章 實驗結果與分析 51
9.1 實驗環境 51
9.2 系統實作 51
9.3 圖形拓撲建立 54
9.3.1 介面與設定 54
9.3.2 圖形拓撲物件追蹤實驗結果與分析 59
9.4 偵測符合條件路徑事件 63
9.4.1 介面與設定 63
9.4.2 實驗結果與分析 64
9.5 偵測警戒區域發生異常事件 67
9.5.1 介面與設定 67
9.5.2 實驗結果與分析 67
第10章 結論 69
10.1 結論 69
10.2 未來展望 69
參考文獻 70
論文參考文獻:[1] I. K Sethi, R. Jain, “Finding trajectories of feature points in monocular image sequences” IEEE Trans. On PAMI, Jan 1987.
[2] M. Fathy and M. Y. Siyal, “An Image Detection Technique Based on Morphological Edge Detection and Background Difference for Real-time Traffic Analysis,” Pattern Recognition Letters, Vol.16, No.12, pp. 1321-1330, 1995.
[3] C. A. Christopoulos and W. Philips, ”Segmented Image Coding:Techniques and Experimental Results,” Signal Processing: Image Communication, Vol. 11, pp. 63-80, 1997.
[4] C. Kim. and J. N. Hwang, “Fast and Automatic Video Object Segmentation and Tracking for Content-Based Applications,” IEEE Trans. on Circuits System Video Technology, Vol. 12,pp.122-129. 1999.
[5] E. Durucan and T. Ebrahimi, “Change Detection and Background Extraction by Linear Algebra,” Proceedings of the IEEE, Vol. 89, No. 10, pp.1368-1381, 2001.
[6] S. Dockstader and A. M. Tekalp, “Multiple Camera Tracking of Interacting and Occluded Human Motion,” Proceedings of the IEEE, Vol. 89, No. 10, pp.1441-1455, 2001.
[7] I. K Sethi, R. Jain, “Finding trajectories of feature points in monocular image sequences” IEEE Trans. On PAMI, Jan 1987.
[8] J. H. Guo and T. S. Wang, “A Real-time Image Segmentation Scheme for Networked Visual Surveillance Systems,” Proceedings of the NCS, pp. 90-97, Taipei, Taiwan, 1999.
[9] O. Javed and M. Shah, “Tracking and Object Classification for Automated Surveillance,” Proc. European Conf. Computer Vision, Vol. 4, pp. 343–357, 2002.
[10] W. Y. Ma and B. S. Manjunath, ”Edge Flow: A Framework of Boundary Detection and Image Segmentation”, Proceeding of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 774-749, 1997.
[11] P. Remagnino, A. I. Shihab and G. A. Jones, “Distributed intelligence for multi-camera visual surveillance,” Pattern Recognition, Vol. 37, pp.675-689, 2004.
[12] J. Black, D. Makris and T. Ellis, ”Hierarchical database for multi-camera surveillance system,” Pattern Analysis Application, pp. 430-446, 2005.
[13] C. Regazzoni , V. Ramesh and G. Foresti, ”Special Issue on Video Communications, Processing, and Understanding for Third Generation Surveillance System,” Proceedings of the IEEE, Vol. 89, No. 10, pp.1355-1367, 2001.
[14] Jose M. Molina, Jesus Garcia, Francisco J. Jimenez and Jose R. Casar, “Surveillance multisensor management with fuzzy evaluation of sensor task priorities”, Engineering Applications of Artificial Intelligence, Vol. 15, pp.511-527, 2002.
[15] M. Valera and S. A. Velastin, “Intelligent Distributed Surveillance Systems”, IEEE Proc.Visual Image Signal Process. Vol. 152, No. 2 April 2005.
[16] Robert T. Collins, Alan J. Lipton, Hironobu Fujiyoshi, and Takeo Kanade, “Algorithms for Cooperative Multisensor Surveillance,” Proceedings of the IEEE, Vol. 89, No. 10, October 2001.
[17] D. Chai and A. Bouzerdoum, “A Bayesian Approach to Skin Color Classification in YCbCr Color Space,” TENCON 2000. Proceeding, IEEE, Kuala Lumpur Malaysia, Vol.2, pp.421-424, Sept. 2000.
[18] Marc R. Pearlman and Zygmunt J. Haas, “Determining the Optimal Configuration for the Zone Routing Protocol”, IEEE Journal on Selected Areas in Communications, Vol.17, No.8, Aug. 1999.
[19] ISO/IEC 15938-3:2001, “Multimedia Content Description Interface-Part 3: Visual,” Version 1.
[20] Christian von Hardenberg and Francois Berard, “Bare-Hand Human-Computer Interaction, ” ACM International Conference Proceeding Series, Vol. 15, 2001.
[21] M. J. Lucena, “An Optical Flow Probabilistic Observation Model for Tracking,” Proc. of ICIP, Vol. 1, 2003.
[22] R. Cucchiara, C. Grana, M. Piccardi, and A. Prati, “Detecting Moving Objects, Ghost, and Shadows in Video Streams,” IEEE Trans. Pattern Anal. Machine Intell., Vol. 25, No. 10, pp. 1337-1342, 2003
[23] D. Comaniciu, V. Ramesh, and P. Meer, “Kernel Based Object Tracking,” IEEE Trans. Pattern Anal. Machine Intell., Vol. 25, No.5, pp. 564-557, May 2003.
[24] T. L. Liu, and H. T. Chen, “Real-time Tracking Using Trust-region Methods,” IEEE Trans. Pattern Anal. Machine Intell., Vol. 26, No.3, pp. 397-402, March 2004.
[25] 袁凱群,限制區域非法進入者之偵測,碩士論文,國立中央大學資訊工程研究所,中壢,2005。
[26] 胡冠宇,基於膚色之裸體影像測試之研究,碩士論文,國立成功大學工程科學研究所,台南,2004。
[27] 張傑閩,羽球場中球員位置偵測與追蹤方法,碩士論文,國立臺北科技大學資訊工程研究所,台北,2006。
[28] 鍾國亮,影像處理與電腦視覺,台北:東華書局,2002,第138-157頁。
[29] Motion Detection, http://www.codeproject.com/cs/media/Motion_Detection.asp