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研究生:張李亞迪
研究生(外文):Chang, Lee-Ya-Ti
論文名稱:光流應用於自我移動估測
論文名稱(外文):Egomotion Estimation via Optical Flow
指導教授:田仲豪
指導教授(外文):Tien, Chung-Hao
口試委員:陳智弘陳政寰吳金典
口試委員(外文):Chen, Jye-HongChen, Ch-HuWu, Chin-Tien
口試日期:2017-12-18
學位類別:碩士
校院名稱:國立交通大學
系所名稱:光電工程研究所
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:2017
畢業學年度:106
語文別:中文
論文頁數:45
中文關鍵詞:自我運動光流相位關聯相機模型
外文關鍵詞:ego-motionoptical flowphase correlationcamera model
相關次數:
  • 被引用被引用:0
  • 點閱點閱:217
  • 評分評分:
  • 下載下載:29
  • 收藏至我的研究室書目清單書目收藏:0
自我移動估測對於載具的自動控制是必要的資訊之一,而隨著電腦視覺領域的相關技術應用於載具愈來愈廣泛,若能開發出以電腦視覺為基礎的自我移動估測系統,不僅能夠在傳統自我移動估測方法無法使用的情況下也能工作,而且也可以用來搭配其他電腦視覺的應用,因此本研究的目標為開發基於電腦視覺的自我移動估測系統。
本研究目標為以影像光流法來實現即時的自我移動估測,因此本文會探討不同影像光流的計算方法,找出最適合即時運算的方法,然後描述如何利用相機模型,將影像移動量轉換成實際的移動量,最後再以實驗驗證系統的性能表現。
Egomotion estimation is an essential information for autopilot. As the massive development of computer vision in the modern world, there are a lot of applications for vehicles which based on computer vision. There are many advantages to develop egomotion estimation technique based on computer vision. For example, it can be used for egomotion estimation when traditional methods are not available. At the same time, it can cooperate with other computer vision techniques. Therefore, we propose an egomotion estimation system based on computer vision in this research.
The goal in this research is to develop a real time egomotion estimation system via optical flow. In this paper, we discuss and compare different calculation methods of optical flow to find the moderate technique for our objective. Also, we describe how to transform optical flow to physical translation based on camera model. Finally, we design an experiment for the performance verification.
摘要 i
Abstract ii
誌謝 iii
圖目錄 vi
表目錄 vii
第1章 緒論 1
1.1 研究背景 1
1.2 研究目的 2
1.3 論文架構 2
第2章 相關研究 3
2.1 全球定位系統 (Global Positioning System) 3
2.2 慣性導航系統 (Inertial Navigation System) 3
2.3 單應矩陣分解法 (Homography Matrix Decomposition) 4
2.4 離焦雷射散斑影像法 (Speckle Defocus Imaging) 5
第3章 影像光流計算 6
3.1 特徵點檢測 (Feature Detection) 6
3.2 光流方程式 (Optical Flow Equation) 9
3.3 盧卡斯-卡納德方法 (Lucas-Kanade Method) 10
3.4 霍恩-舒克方法 (Horn-Schunck Method) 12
3.5 相位相關法 (Phase-Only Correlation Method) 14
3.5.1 相位相關函數 (Phase-Only Correlation Function) 14
3.5.2 子像素級影像移動量計算 15
3.6 光流計算方法比較 19
第4章 相機模型 23
4.1 針孔相機模型 (Pinhole Camera Model) 23
4.2 齊次坐標 (Homogeneous Coordinates) 24
4.3 相機投影矩陣 (Camera Matrix) 24
4.4 相機校正 (Camera Calibration) 27
4.5 自我移動估測 (Egomotion Estimation) 30
第5章 實驗 31
5.1 實驗系統 31
5.1.1 系統架構 31
5.1.2 演算法實作 34
5.2 實驗結果 36
5.3 問題與討論 40
第6章 結論與未來展望 41
6.1 結論 41
6.2 未來展望 42
參考文獻 43
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