以球形及圓柱投影之環景影像產製三維點雲

The Generation of 3D Point Clouds from Spherical and Cylindrical Panorama Images

10.6574/JPRS.201812_23(4).0004

張智安(Tee-Ann Teo)；張正岳(Cheng-Yueh Chang)

環景影像 ； 多相機系統 ； 三維點雲 ； Panorama images ； Multi-camera system ； 3D point clouds

航測及遙測學刊

23卷4期（2018 / 12 / 01）

273 - 284

繁體中文

使用多相機同步取樣系統於三維點雲產製時，可採用原始多相機相幅式影像(Frame image)或拼接後之環景影像(Panorama image)。環景影像為一涵蓋360度之影像，多相機影像可使用不同的投影方式產生環景影像，例如球形投影及圓柱投影。本研究探討不同投影方式之多相機影像於三維點雲重建，不同投影影像包含：(1)未拼接原始相幅式影像、(2)拼接後球形投影環景影像、(3)拼接後圓柱投影環景影像。本研究採用五台GoPro Hero4相機同步取樣系統，由於同步取樣有些微時間秒差的問題，必須將各相機影像先進行時間同步，再進行環景影像拼接。成果分析採用定性及定量分析，定性分析以視覺化比較不同投影產製之三維點雲；定量分析以全測站量測之獨立檢核點進行精度分析。實驗資料為一室內空間之多測站影像攝影測量，實驗顯示未拼接多視角原始相幅式影像之三維平均誤差約為4 cm，而拼接後環景影像之三維平均誤差約為7 cm，因多視角原始相幅式影像之交會幾何較佳，故精度較環景影像高。比較球形投影及圓柱投影環景影像之三維點雲，圓柱投影產生的點雲數量較高，但相對所需運算時間較久。

Three-dimensional point clouds can be generated using multi-frame images or multi-panorama images taken by a multi-camera system. Panorama image is a 360-degree image covering in horizontal and vertical directions. The multi-camera system produces different types of panorama images, such as spherical projection and cylindrical projection. The objective of this study is to compare the 3-D point clouds generated from frame images and panorama images using different projection modes. Five GoPro Hero4 cameras were integrated into a multicamera system and applied to acquire three type of images (i.e., original frame images, spherical panorama images and cylindrical panorama images) in a video mode. Because of the slight time lag problem in synchronous images taking, each camera implements time synchronous before stitching panorama images. The comparison includes quantitative and qualitative analysis. The experimental results indicated that the accuracies of frame images and panorama images were 4 cm and 7 cm in an indoor space. The frame images provided better geometric constraint and offered higher efficiency than panorama images. To compare spherical and cylindrical panorama images, the number of points from cylindrical images was larger than spherical images. Consequently, the computational time of cylindrical images was also slightly longer than spherical images.

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