Accurate Georegistration of Point Clouds Using Geographic Data
Accurate Georegistration of Point Clouds Using Geographic Data
复制标题
使用地理数据对点云进行准确的地理配准
DOI：
10.1109/3dv.2013.13
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Noah Snavely
中科院分区：
文献类型：
--
作者：
Chun;Kyle Wilson;Noah Snavely
互联网包含了关于我们世界的丰富地理信息，包括3D模型，街道地图和许多其他数据源。这些信息对于计算机视觉应用可能很有用，例如户外互联网照片的场景理解。然而，将这些数据用于视觉应用需要通过估计位置、方向和焦距，在地理坐标系内精确地对齐从野外拍摄的输入照片。为了解决这个问题，我们提出了一个系统，用于调整3D结构从运动点云，从互联网图像，现有的地理信息源，包括谷歌街景照片和谷歌地球3D模型。我们表明，我们的方法可以在这些数据源之间产生准确的对齐，从而能够准确地将地理数据投影到从互联网收集的图像中，通过“谷歌搜索”使用Google Earth等来源的图像深度图。
The Internet contains a wealth of rich geographic information about our world, including 3D models, street maps, and many other data sources. This information is potentially useful for computer vision applications, such as scene understanding for outdoor Internet photos. However, leveraging this data for vision applications requires precisely aligning input photographs, taken from the wild, within a geographic coordinate frame, by estimating the position, orientation, and focal length. To address this problem, we propose a system for aligning 3D structure-from-motion point clouds, produced from Internet imagery, to existing geographic information sources, including Google Street View photos and Google Earth 3D models. We show that our method can produce accurate alignments between these data sources, resulting in the ability to accurately project geographic data into images gathered from the Internet, by ``Googling'' a depth map for an image using sources such as Google Earth.