三維重建(3D Reconstruction)技術是利用多張多視角影像，將二維投影恢復物體三維空間之方法，類似人類雙目定位概念；從平面影像還原成立體模型如真實物體，表現出更豐富的細節資訊，而三維模型的呈現實現於生活廣泛之應用。
本研究以行動裝置為平台，對物體進行環繞拍攝取樣，透過運動恢復結構之影像演算法，無須事先校正相機參數，即計算出相機姿態與場景幾何相對關係；此外，加上感測器的地理資訊輔助，其強健穩定的特性，二次驗證定位方法，對齊校正座標，增加三維模型之精準度、提高運算效能。

3D reconstruction is the process of capturing the shape and appearance of real objects from the keyframe of different viewpoint. Through the projection of two-dimensional materials to restore three-dimensional space, which is similar to a binocular vision for the position. Nowadays, a 3D model is implemented in many applications, from an image reverts into a stereoscopic model as the original real object, that can be given more details of texture and structure.

First, based on the mobile device to scan around the object for video recording, using structure from motion(SfM) algorithm to calculate the relationship of camera position and scene geometric. Meanwhile, at the scanning stage, the sensor data are acquired along with tracks of features in the video. All these data are used to build a camera trajectory using above image techniques after scanning is completed. According to information support of sensor geography with robustness and stability, which can be demonstrated the second validation on positioning, not only enhance the accuracy of the 3D model, but also improve the efficiency.

附圖目錄 III
附表目錄 IV

第一章 緒論 1
1.1 研究動機 1
1.2 研究目的 2
1.3 研究範圍與限制 3
1.4 論文章節架構 3

第二章 文獻探討 5
2.1 現有技術概況 5
2.2 背景知識及相關原理 7
2.2.1 特徵擷取 8
2.2.2 相機場景幾何 12
2.2.3 感測器資訊 17

第三章 研究方法 22
3.1 系統架構 22
3.2 關鍵畫面截取 (KeyFrame Extraction) 25
3.3 從運動求得結構 (Structure from Motion, SfM) 27
3.3.1 三維重建 29
3.4 感測器資訊輔助 (IMU sensor Information) 30
3.4.1 定義座標系 30
3.4.2 GPS優先使用法 34
3.4.3 7-DoF相似度轉換(Similarity Transform) 37

第四章 實驗規劃 42
4.1 實驗環境 42
4.2 實驗 43
4.2.1 實驗一：以物體為對象 43
4.2.2 實驗二：以感測器資訊為輔助 53
4.2.3 實驗三：以影像張數為對象分析 56

第五章 結論 59
5.1 未來工作 59

附錄A 60
附錄B 68
參考文獻 79

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