Multiview Geometry for Texture Mapping 2D Images Onto 3D Range Data

The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates multiview geometry and automated 3D registration techniques for texture mapping 2D images onto 3D range data. The 3D range scans and the 2D photographs are respectively used to generate a pair of 3D models of the scene. The first model consists of a dense 3D point cloud, produced by using a 3D-to-3D registration method that matches 3D lines in the range images. The second model consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. This paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model....

• Type: Conference
• Year: 2006
• Where: CVPR
• Authors: Lingyun Liu, Gene Yu, George Wolberg, Siavash Zokai
• Keywords: Computer Vision, CVPR 2006, Dense 3d Point, Dense Model, Large-scale Urban Scenes, Multiview Geometry, Sparse 3d Point