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Registration and integration of textured 3D data

机译:配准和集成纹理3D数据

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In general, multiple views are required to create a complete 3D model of an object or of a multi-roomed indoor scene. In this work, we address the problem of merging multiple textured 3D data sets, each of which corresponds to a different view of a scene. There are two steps to the merging process f registration and integration. To register, or align, data sets we use a modified version of the iterative closest point (ICP) algorithm; our version, which we call color ICP, considers not only 3D information, but color as well. We show that the use of color decreases registration error significantly when using omnidirectional stereo data sets. Once the 3D data sets have been registered, we integrate them to produce a seamless, composite 3D textured model. Our approach to integration uses a 3D occupancy grid to represent likelihood of spatial occupancy through voting. In addition to occupancy information, we store surface normal in each voxel of the occupancy grid. Surface normal is used to robustly extract a surface from the occupancy grid; on that surface we blend textures from multiple views.
机译:通常,需要多个视图来创建对象或多房间室内场景的完整3D模型。在这项工作中,我们解决了合并多个纹理3D数据集的问题,每个数据集都对应于一个场景的不同视图。合并过程包括两个步骤:注册和集成。为了注册或对齐数据集,我们使用迭代最近点(ICP)算法的修改版;我们称为彩色ICP的版本不仅考虑3D信息,还考虑颜色。我们显示,使用全向立体声数据集时,使用颜色会显着降低配准误差。一旦注册了3D数据集,我们便将其集成以生成无缝的合成3D纹理模型。我们的集成方法使用3D占用率网格通过投票来表示空间占用率的可能性。除了占用信息以外,我们还将表面法线存储在占用网格的每个体素中。表面法线用于从占用栅格中可靠地提取表面;在该表面上,我们从多个视图混合纹理。

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