臺灣博碩士論文加值系統

在日常生活中，監控系統被廣泛用在許多地方，如：大廳、辦公室、工廠與學校。現在的監控系統都可提供網路功能，系統管理員可以透過網路進行遠端控制去監控感興趣的目標/環境狀況。然而，現有的監控攝影機大多都佈署在固定的位置，像是天花板或牆壁。為了達到完全覆蓋或捕捉到環境中的所有目標物，往往需要設置大量的攝影機才能實現，意味著成本提高。此外，意外事件並不會隨時發生，大部分的監控畫面都屬於冗餘的資料。如果我們可以在事件發生時馬上捕捉到關鍵畫面，此監控影像將是非常重要的。透過結合攝影機與行動載具，如：相機滑軌、自走車機器人或無人飛行器，我們可賦予攝影機移動能力。在本論文中，我們利用相機滑軌建立可移動監視器，並設計一套智慧型監控系統來捕獲環境中的關鍵畫面。從模擬結果可以看出，我們提出的系統可以在短時間內捕捉到事件，並且維持良好的覆蓋率。此外，我們亦透過實作模型來展示此系統的效能。當事件發生時，攝影機會立即跑去相應位置來捕捉關鍵畫面，表示它確實能夠提供可靠地監控服務。

Surveillance system is widely used for many purposes, such as: hall, office, factory and school. Nowadays most surveillance systems provide network function, thus the operator is able to monitor the target/situation of interested area remotely. However, most cameras are deployed at a fixed position, for example, ceiling or wall. In order to reach full coverage or capture all target objects in the environment, we have to deploy many cameras to achieve it, which leads to high cost. Nevertheless, most cameras are not in use because of no events occur, the video data is redundancy. If we can capture the key video when new events occur, the video data is significant. The goal can be reached by combining camera with moving ability, ex: camera slide track, camera on robot or drone. In this thesis, we propose a smart surveillance system with movable cameras to capture the key video based on camera slide track. From simulation results, most events can be captured in time and keep high coverage ratio. We also implement a prototype to demonstrate the performance. Via the prototype, we show that the smart surveillance system has the ability to provide reliable surveillance.

摘要 i
Abstract ii
Acknowledgement iii
Table of Contents iv
List of Tables vi
List of Figures vii
I. Introduction 1
II. Related Works 4
III. System Model of Moving Camera 7
3.1. Target 7
3.2. Track 8
3.3. PTZ (Pan-Tilt-Zoom) Camera 9
3.4. Monitoring Requirement 11
3.4.1. Resolution 11
3.4.2. View of Angle (VA) 12
3.4.3. Line of Sight 12
3.5. Configuration Time 13
3.6. Problem Formulation 15
IV. Greedy Algorithm 18
4.1. Find Next Position of Camera 19
4.2. Determine FoV of Camera 25
4.3. Time Complexity Analysis 28
V. Simulation Evaluation 29
5.1. Number of Deployed Cameras 31
5.2. Number of Deployed Objects 33
VI. Implementation 36
6.1. System Design 36
6.2. System Implementation 38
6.2.1. Specification of the System 38
6.2.2. Procedure of the System 40
6.3. Demonstration of Real Environment 41


VII. Conclusion 45
References 46

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