利用SGM和PMVS演算法進行MUAV影像密匹配之比較分析

Comparision Dense Matching of MUAV Images via SGM and PMVS

林迪詒(Di-Yi Lin) ； 謝嘉聲(Chia-Sheng Hsieh)

《航測及遙測學刊》 22卷3期 (2017/09) Pp. 193-203

https://doi.org/10.6574/JPRS.2017.22(3).4

摘要

現今無人機(Unmanned Aerial Vehicle, UAV)技術發展成熟，在拍攝影像上兼具即時性和方便性，藉由拍攝而得的影像可快速重建出近似實景的三維資訊。UAV影像在空間資訊的應用大致區分為環繞拍攝整棟建物建立完整三維模型之應用及垂直拍攝地形產製正射影像製圖使用。目前因相關技術發展快速，在影像處理如特徵點偵測、特徵點匹配大都有合適的演算法進行處理，惟有在稠密點雲匹配計算過程中，尚未有較理想的處理方法。為探討不同密匹配方法的特色及適用性，本研究中選取不同理論基礎且較廣泛使用的兩種密匹配方法進行比較，以半全域演算法(Semi-Global Matching, SGM)及全域演算法(Global Method)中基於區塊方法(Patch-based Multi-view Stereo, PMVS)匹配，分別將兩種密匹配演算法應用在進行環繞拍攝之單一古蹟建物及垂直拍攝校園之影像中比較分析，藉由實務之比較分析，提供利用UAV拍攝影像重建三維點雲處理之參考。

關鍵字

UAV ； 三維建模 ； 密匹配 ； SGM ； PMVS

並列摘要

The Unmanned Aerial Vehicle (UAV) has been developed mature. It is both immediacy and convenience on the field of images shooting. The three-dimension information that close to real can be constructed via the images which taken from UAV. The utilizing on geospatial of UAV is construct complete three-dimension model from shooting a building surround and produce orthophoto from shooting topography vertical. There are good algorithms both on the field of set up relative relationship between ground and images and calculating camera parameters because of the well developing of relative technique; only on the field of the procedure of calculating dense point cloud has not been developed a suitable method. In order to investigate characteristics and applicability of different dense matching, two methods from different theoretical basis and both widely used are chosen in this study, including Semi-Global Matching (SGM) and Patch-based Multi-view Stereo (PMVS) from Global Method. We use these two methods to analyze the images taking from shooting a historical sites surround and campus vertical. The result can be a reference for construct three-dimension point cloud from the images taking from UAV.

並列關鍵字

UAV ； 3D Modeling ； Dense Matching ； SGM ； PMVS