過去的移動物體偵測技術大都用於大樓監控系統(surveillance system)，由於使用靜止相機，即靜止背景在一段時間內都在畫面中呈現固定不動，所以這樣的監控系統可以輕易的建立背景模型，再利用背景相減法(background subtraction)，即可扣除畫面中不變的靜止背景區，未被減去的殘餘區塊即為移動物體所在區域。
當前述監控系統所使用之演算法用於盲人導航、汽車防撞等具有自我移動的裝置系統時，相機拍攝的一連串畫面將因為像機具有自我運動，而導致靜止背景在畫面中亦會隨著相機的自我運動而改變，靜止物體與移動物體在畫面中將變得難以區分。許多既有文獻採取對整張影像使用相同平面轉換參數將第一時間影像補償至第二時間，以達成背景補償目的，然而遠近不同景物並無法用同一平面轉換良好補償之，故部分文獻使用多次疊代來達到全域最佳化的方式以求取良好背景補償，但這樣的策略卻導致計算量龐大，故本研究改使用色彩分割作為景物切割依據，再依據各色塊給予不同平面轉換參數補償之，以色塊為單位之背景補償可涵蓋平移、旋轉、縮放等因素，明顯優於既有文獻以整張影像為單位折中的平移補償方式，而且使用色彩分割比起疊代求取全域最佳化的方式節省大量的運算時間。對於前後時間控制點匹配問題則根據固有的投影幾何關係提出搜尋區域概念，直接預估控制點下一時間可能位置，大幅縮減搜尋區域，降低運算時間，也同時提高正確匹配結果。
根據前述對既有文獻的改良，本研究所提出之演算法運算量低，而且可達到比既有文獻更優良的背景補償結果，強健快速的特性使本演算法更能達成即時偵測目的。

目 錄 I
圖 目 錄 III
表 目 錄 VI
第一章 簡介 1
1. 1問題背景與問題描述 1
1. 2文獻回顧 2
1.2.1 用於移動物體偵測之硬體種類及其對應技術 3
1.2.2 彩色數位相機移動物體偵測技術 6
1. 3研究方法 10
1. 4適用範圍與論文架構 12
第二章 適用於彩色數位雙相機之移動物體偵測技術 13
2. 1極幾何與基本矩陣 (epipolar geometry and fundamental matrix) 13
2. 2相機模型 (camera model) 16
2. 3視差圖技術 (disparity map) 18
2. 4 均值位移色彩分割 (mean shift color segmentation) 21
2. 5 平面投影轉換 (planar transformation) 24
2. 6 瞬時差異法 (temporal difference) 25
第三章 位於移動平台上之移動物體偵測技術 26
3. 1 快速強健之移動平台上之移動物體偵測技術 26
3.1. 1 測試前校正 29
3.1. 2 左右影像控制點對應與深度計算 30
3.1. 3 前後影像控制點對應 31
3.1. 4 色彩分割及計算二維平面補償參數 49
3.1. 5 背景補償及瞬時相減法 50
第四章 實驗結果與分析比較 52
4. 1 加入搜尋區域概念之於前後時間對應結果 52
4. 2 物深度分佈複雜場景測試結果 58
第五章 結論 69
5. 1本研究之貢獻 69
5. 2本研究的實用價值及未來發展方向 70
參考文獻 72

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