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The generation of accurate, watertight, three-dimensional models of environments are often crucial for the purposes of scientific study and infrastructure management. Most commonly, such models are acquired by using range sensors producing point clouds, and further processing steps are required for the construction of a surface model. We used a mobile lidar to map several kilometers of a natural cave system in order to obtain 3D volumetric models for use in scientific research studying the local palaeo-climatic record. For unstructured and GPS-denied environments, such as cave systems, the process of acquiring a complete map is difficult and further complicated by limited mobility within the cave. During the mapping process, many unwanted measurements occur due to occlusions from moving objects such as other people present in the cave. Most common point cloud surface reconstruction techniques are not designed to deal these occlusions; i.e., they require manual cleanup of the data set or are not capable of generating watertight surfaces. The large scale of the environments introduces the additional challenge of dealing with memory limitations. We propose a new volume-based approach to reconstruct a watertight surface from range measurements of enclosed environments without limitation on the scale of the collected data. Our approach carves all unoccupied voxels from the sensor to a triangulated and rasterized surface between successive scans, which is intended to fill in the missing data between the scan rays. The surface is then constructed from the isosurface between unoccupied and unknown cells. By decomposing the space, we are able to handle large-scale data without exceeding the memory limitation of a standard PC, at the cost of some additional computation time. The algorithm has been evaluated across several datasets within a variety of environments and observed to build more complete volumetric models than a simple space carving approach. We have mapped severa- kilometers of cave networks and, with the described method, produced watertight reconstructions suitable for further scientific analysis.
Date of Conference: 25-30 Sept. 2011