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研究生:陳昰亘
研究生(外文):Shin-Ken Chen
論文名稱:用球型攝影機做電腦視覺的物件追蹤
論文名稱(外文):Computer Vision Target Tracking Using a Fast Dome Camera
指導教授:林啟芳
指導教授(外文):Chi-Fang Lin
學位類別:碩士
校院名稱:元智大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:中文
論文頁數:53
中文關鍵詞:目標追蹤色彩物體擷取球型攝影機
外文關鍵詞:Target TrackingColor SegmentationDome Camera
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本論文的主要目的是在攝影監控系統中提出物件追蹤的方法,利用可以旋轉的球型攝影機去追蹤與放大被鎖定的物體,以便獲得被鎖定物體的較清晰影像。方法內容主要是利用一部個人電腦來擷取球型攝影機所拍攝到的畫面,分析畫面的色彩並透過兩次的連續可適性質量中心偏移(CAMSHIFT)演算法找出鎖定物體的位置及大小。第一次連續可適性質量中心偏移演算法是用來修正預測的形狀遮罩位置,第二次則是計算追蹤物體的偏移量進而找出物體在畫面中的位置及大小。計算連續影像中物體的位置及大小變化可以得知物體的移動方向與速度等資訊,再根據這些資訊來控制球型攝影機,讓攝影機鏡頭可以隨著被鎖定物體移動。

This paper presents a method to track an object in a surveillance system using a dome camera, having the abilities of pan, tilt and zooming. The main purpose of tracking is to track the trajectories of the moving target, and obtain better images of the target. The content of the method includes capturing images, analyzing the color of images, and performing a tracking algorithm twice to find the position of the target. The first time of the tracking algorithm is to correct the predicted position of the shape mask, and the second time is to find the position and the size of the target. Positions of the target in continuous frame rate will give information about the trajectories that the target moves. Finally, according to the obtained information, we could control the dome camera so that it can follow the moving target.

中文摘要 i
Abstract ii
目錄 iii
圖目錄 v
第 1 章、 前言 1
1.1 動機與目的 1
1.2 相關研究 1
1.3 論文架構 4
第 2 章、 概念 5
2.1 前言 5
2.2 硬體及軟體架構 5
2.2.1 硬體架構 5
2.2.2 軟體架構 6
2.3 系統介紹 9
第 3 章、 所提方法 12
3.1 前言 12
3.2 影像處理追蹤單元 12
3.2.1 HSI轉換並產生多維度特徵影像 14
3.2.2 產生特徵機率分佈影像 16
3.2.3 特徵機率分佈影像套用遮照 18
3.2.4 利用質量中心計算來追蹤物體 19
3.2.5 調整遮罩位置並重新套用遮照與追蹤物體 20
3.2.6 產生新的遮照 21
3.3 球型攝影機動作單元 22
3.3.1 求出球型攝影機需要的旋轉速度 23
3.3.2 套用修正曲線 28
3.3.3 縮放的處理 28
3.4 球型攝影機旋轉速度預測單元 28
3.4.1 物理特性的計算 29
3.4.2 球型攝影機的限制 29
第 4 章、 實驗結果及討論 31
4.1 實驗環境介紹 31
4.2 實驗結果 31
第 5 章、 結論與未來工作 36
5.1 結論 36
5.2 未來的發展 37
參考文獻 39

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http://developer.intel.com/technology/itj/q21998/articles/art_2.htm
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[15] Intel® Open Source Computer Vision Library from:
http://sourceforge.net/projects/opencvlibrary
[16] D. Simon, “Kalman filtering,” Innovatia Software, from: http://www.innovatia.com/software/papers/kalman.htm
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