遺留物及持有人自動偵測並具關鍵影像提供能力之視訊監控系統

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姓名

祝珮軒(Pei-Hsien Chu) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

遺留物及持有人自動偵測並具關鍵影像提供能力之視訊監控系統
(A Video Surveillance System for Automatic Abandoned Object and Owner Detection with Keyframe Providing Capability)

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摘要(中)

建立一套智慧型監控系統，其能夠自動地分析影像來偵測出在無人注意的環境之中所被置放的遺留物，並且亦能夠自動地提供關鍵畫面以代替利用人力資源來監控環境。為了偵測並描述完整之遺留物事件，希望不但能偵測到遺留物之外，還能知道遺留物是誰遺落下來的，並且用關鍵畫面以描述整個遺留物事件。
本篇論文將系統分為三個主要部份，第一部份利用兩層的背景架構與背景時間差異法找出靜態的場景變化，結合邊緣資訊和特徵，使用倒傳遞類神經網路分類，以偵測出場景之中的遺留物。第二部分是先統計追蹤物的顏色分佈機率，再透過比對分析其身上是否有物品缺失，當偵測到有物品缺失之後，會對此缺失的物品建立一個混合高斯模型一同與影像建入資料庫中。以上兩部份為平行獨立偵測，當系統偵測到有遺留物的同時也偵測到有人身上有物品遺失之後，系統才會進入第三部份,利用偵測到的遺留物資訊與資料庫中的模型進行比對，搜尋是否有可描述此遺留物事件的關鍵影像。
一旦有遺留物被偵測出來，或是有人遺失物品被偵測到，系統皆會發出警訊，使相關人員提高警覺或相關反應措施。若同時有兩種警訊觸發，此時系統會再去判斷兩個警訊的關聯性，若確認為同一事件，便會提供關鍵影像以讓相關人員能夠立即的做出反應。由實驗可證實所提出偵測遺留物的方法是可行且有效的。

摘要(英)

In this thesis, an intelligent video-based surveillance system for the detection of dangerous situations related to the presence of abandoned objects in unattended or guarded environment is presented. In the proposed system, image processing content-based retrieval capabilities have been added to make the operator inspection task easier. When a potential abandoned object event is detected, the operator is notified and the system provides a keyframe for interpreting the incident.
In addition to tracking a moving person and deciding if he drops an object automatically, the system also detects the presence of abandoned object in a monitored area simultaneously. Depending on the detection of either an abandoned object or someone abandoning an object, different alarms will be signaled. Then, the system finds the relationship between the causes of the alarms. If it is verified that someone has lost the abandoned object, in other words, the owner and abandoned objects are detected, the system will alert the operator and provide him the keyframe, i.e., semantic information of which relating to both of the dangerous object and the person who left it in the surveillance environment.
Experimental results are illustrated in terms of abandoned object detection, owner detection, keyframe detection, the probability of correct detection of abandoned objects as well as examples of abandoned objects event sequences. The results demonstrate that the proposed system is feasible and effective in abandoned object detection.

關鍵字(中)

★ 視訊監控系統
★ 遺留物

關鍵字(英)

★ Video Surveillance system
★ abandoned object

論文目次

Abstract I
摘要 II
誌謝 III
目錄 IV
附圖目錄 VI
表格目錄 VIII
第一章緒論 - 1 -
1.1 研究動機 - 1 -
1.2 相關研究 - 2 -
1.3 系統流程 - 4 -
1.4 論文架構 - 6 -
第二章遺留物偵測 - 7 -
2.1背景模組 - 10 -
2.2靜態目標物偵測 - 12 -
2.2.1背景時間差異法 - 12 -
2.2.2雜訊去除 - 14 -
2.2.3陰影去除 - 16 -
2.3遺留物確認 - 18 -
2.3.1邊緣資訊 - 19 -
2.3.2分類 - 21 -
2.3.2.1物體特徵擷取 - 21 -
2.3.2.2倒傳遞類神經網路 - 24 -
第三章遺留物持有人者偵測 - 28 -
3.1前景物偵測 - 28 -
3.2前景物追蹤 - 30 -
3.3區塊顏色比對 - 34 -
3.3.1 Color Coherence Histogram - 34 -
3.3.2 Fuzzy Color Histogram - 37 -
3.4高斯模組 - 42 -
3.4.1資料空間轉換 - 42 -
3.4.2高斯混合模型 - 46 -
3.4.3高斯混合模型訓練 - 48 -
第四章關鍵影像模組 - 53 -
4.1影像檢索資料庫建立 - 54 -
4.2事件對應關係連結 - 56 -
4.3關鍵影像擷取 - 57 -
第五章實驗結果 - 59 -
5.1背景模組 - 59 -
5.2前景物擷取 - 60 -
5.3前景物追蹤 - 61 -
5.4遺留物偵測 - 62 -
5.5遺留物持有人偵測 - 66 -
5.6關鍵影像擷取 - 70 -
第六章結論與未來工作 - 75 -
6.1結論 - 75 -
6.2未來工作 - 76 -
參考文獻 - 77 -

參考文獻

[1]J. Wang and W. Ooi, “Detecting static objects in busy scenes”, Department of Computer Science, Cornell University, Technical Report TR99-1730, Feb 1999
[2]E. Stringa and C. S. Regazzoni, “Real-time video-shot detection for scene surveillance applications”, IEEE Transactions on Image Processing, Vol. 9, Issue 1, Page(s):69-79, Jan 2000
[3]G. L .Foresti, L. Marcenaro and C. S. Regazzoni, “Automatic detection and indexing of video-event shots for surveillance applications”, IEEE Transactions on Multimedia , Vol. 4, Issue 4, Page(s):459 – 471 Dec 2002
[4]M. D. Beynon, D. J. VanHook, M. Seibert, A. Peacock and D. Dudgeon, “Detecting abandoned packages in a multi-camera video surveillance system”, IEEE Conference on Advanced Video and Signal Based Surveillance, Page(s):221 - 228 Jul 2003
[5]M. Spengler and B. Schiele, “Automatic Detection and Tracking of Abandoned Objects”, In Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, Oct 2003
[6]Y. L. Tian, M .Lu, and A. Hampapur, “Robust and Efficient Foreground Analysis for Real-time Video Surveillance”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), Vol. 1, Page(s):1182 - 1187 Jun 2005
[7]B. Chen and Y. Lei, “Indoor and outdoor people detection and shadow suppression by exploiting HSV color information”, Proceedings of the Fourth International Conference on Computer and Information Technology, Page(s):137–142,14-16 Sep 2004
[8]C. R. Wren, A. Azarbayejani, T. Darrell and A. P. Pentland, “Pfinder: Real-Time Tracking of the Human Body”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 7, pp. 780-785, Jul 1997.
[9]T. Cormen and al. Introduction to Algorithm. Second Edition, The MIT Press, 2001
[10]A. Prati, I. Mikic, M. M. Trivedi and R. Cucchiara, “Detecting moving shadows: algorithms and evaluation”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25, No. 7, Jul 2003
[11]R. Cucchiara, C. Grana, A. Prati and R. Vezzani, “Computer vision system for in-house video surveillance,” IEE Proc.-Vis. Image Signal Process, Vol. 152, No. 2, Apr 2005
[12]A. Cavallaro, O. Steiger and T. Ebrahimi, “Tracking video objects in cluttered background”, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 15, No. 4, Apr 2005.
[13]J. Connell, A.W. Senior, A. Hampapur, Y-L Tian, L.Brown, and S. Pankanti, “Detection and Tracking in the IBM PeopleVision System”, IEEE ICME, Jun 2004
[14]蘇木春, 張孝德, “機器學習：類神經網路、模糊系統以及基因演算法則”, 全華科技圖書股份有限公司, 2003.
[15]J. Han and K. K Ma, “Fuzzy Color Histogram and Its Use in Color Image Retrieval”, IEEE Transactions on Image Processing, Vol. 11, No. 8, Aug 2002
[16]J.C. Bezdek, “Pattern Recognition with Fuzzy Objective Function Algorithms”, New York: Plenum, 1981.
[17]B. Hill, Th. Roger and F.W. Vorhagen, “Comparative analysis of the quantization of color spaces on the basis of CIELab color-difference formula”, ACM Trans. Graphics, VOL. 16, pp. 109-154, 1997.
[18]P. Dempster, N. M. Laird and D. B. Rubin, “Maximum Likelihood from Incomplete Data via the EM Algorithm”, Journal of the Royal Statistical Society. Series B (Methodological), Vol. 39, No. 1, pp. 1-38, 1977.
[19]I.H.R. Cutler, D. Harwood and L.S. Davis, “Backpack: Detection of People Carrying Objects Using Silhouettes”, Computer Vision, The Proceedings of the Seventh IEEE International Conference, 1999
[20]C. Kim, “Object-Based Video Abstraction for Video Surveillance Systems”, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 12, No. 12, Dec 2002
[21]L. Li, “Fusion of Two Different Motion Cues for Intelligent Video Surveillance”, IEEE Catalogue, CH37239, No. 01, 2001
[22]C. S. Regazzoni and C. Sacchi, “A distributed surveillance system for detection of abandoned objects in unmanned railway environments”, IEEE Transactions on Vehicular Technology, Vol. 49, No. 5, Sep 2000
[23]E. Stringa and C. S. Regazzoni, “Content based retrieval and real time detection from video sequences acquired by surveillance systems”, in Proc. IEEE Int. Conf. Image Processing, Chicago, IL, Oct. 4–7, pp. 138–142 , 1998
[24]C. S. Regazzoni, A. Teschioni, and E. Stringa, “A long term change detection method for surveillance applications”, in Proc. 9th Int. Conf. Image Analysis and Processing, Florence, Italy, pp.485–492., Sep.1997
[25]E. Stringa, F. Soldatini, and C.S. Regazzoni, “Joint video-shot and layer indexing in video-surveillance application”, Image Processing, ICIP 99. Proceedings , 1999

指導教授

范國清(Kuo-Chin Fan)

審核日期

2006-7-6

推文