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 a multiroomed indoor scene. In this work, we address the problem of merging multiple textured 3-D data sets, each of which corresponding to a different view of a scene or object. There are two steps to the merging process: registration and integration. Registration is the process by which data sets are brought into alignment. To this end, we use a modified version of the Iterative Closest Point algorithm (ICP); our version, which we call color ICP, considers not only 3-D information, but color as well. This has shown to have resulted in improved performance. Once the 3-D data sets have been registered, we then 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. The occupancy grid representation allows the incorporation of sensor modeling. The surface of the merged model is recovered by detecting ridges in the occupancy grid, and subsequently polygonized using the standard Marching Cubes algorithm. Another important component of the integration step is the texture merging; this is accomplished by trilinear interpolation of overlapping textures corresponding to the original contributing data sets. We present results of experiments involving synthetic and real scenes. The Robotics Institute, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213