Registration and Integration of Textured 3-D Data

In general, multiple views are required to create a complete 3-D model of an object or of a multi-roomed indoor scene. In this work, we address the problem of merging multiple textured 3-D data sets, each of which corresponds to a different view of a scene or object. There are two steps to the merging process: registration and integration. To register, or align, data sets we use a modified version of the Iterative Closest Point algorithm; our version, which we call color ICP, considers not only 3-D information, but color as well. We show experimentally that the use of color decreases registration error significantly. Once the 3-D data sets have been registered, we integrate them to produce a seamless, composite 3-D textured model. Our approach to integration uses a 3-D 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...

• Type: Conference
• Year: 1997
• Where: 3DIM
• Authors: Andrew Edie Johnson, Sing Bing Kang
• Keywords: 3-D Data Sets, 3DIM 1997, Image Processing, Occupancy Grid, Textured 3-D Data