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Integration of multiple range and intensity image pairs using a volumetric method to create textured 3D models

机译:使用体积方法集成多个距离和强度图像对,以创建带纹理的3D模型

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Abstract: The reconstruction of highly detailed, 3D object models is a major goal of current research. Such models can be used in machine vision applications as well as for visualization purposes. The method presented here assumes that there are multiple range and intensity image pairs of an object, all registered to a global coordinate system. The individual range images are then used to create a surface mesh and the associated intensity images are applied to the surface mesh as a texture map. These multiple, textured, range meshes are then used to update a volume grid - based upon whether a location in the volume grid is known, unknown, or empty - using information that has the highest confidence for any given voxel. The updated volume grid can then be passed through a marching cubes algorithm with adaptive subdivisions to get a fully textured 3D model. The adaptive marching cubes algorithm takes into account additional information concerning edge weights and texture coordinates to give a smoother surface than that produced with standard marching cubes. Once complete, additional, registered intensity images can be applied to the surface of the object. !12
机译:摘要:高度详细的3D对象模型的重建是当前研究的主要目标。这样的模型可以用于机器视觉应用以及可视化目的。此处介绍的方法假定一个对象有多个范围和强度图像对,所有图像对均注册到全局坐标系中。然后,将各个范围图像用于创建表面网格,并将关联的强度图像作为纹理贴图应用于表面网格。然后,使用对任何给定体素具有最高置信度的信息,基于体积网格中的位置是已知的,未知的还是空的,使用这些多个纹理化的范围网格来更新体积网格。更新的体积网格然后可以通过具有自适应细分的行进立方体算法来获得完全纹理化的3D模型。自适应行进立方体算法考虑了有关边缘权重和纹理坐标的其他信息,以提供比标准行进立方体产生的表面更平滑的表面。完成后,可以将其他已配准的强度图像应用于对象的表面。 !12

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