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6 September 2019 An efficient 3D mapping framework
Dmitrii Tihonkih, Vitaly Kober, Artyom Makovetskii, Aleksei Voronin
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Proceedings Volume 11137, Applications of Digital Image Processing XLII; 111372L (2019) https://doi.org/10.1117/12.2529632
Event: SPIE Optical Engineering + Applications, 2019, San Diego, California, United States
Abstract
Reconstruction of 3D map of the observed scene in real space is based on the information on 3D points coordinates. Triangulation is the known method for surface representation in three-dimensional space. Two consistently obtained frames with point clouds corresponds to two partially overlapping triangulated surfaces. There is known an algorithm for the correct construction of the triangulation of the overlapping area. Another approach to the build of a 3D map is the use of surfels. Surfel is a round patch on the surface. The characteristics of the surfels are described by a triple of elements: the position of the surfel, the normal to the surfel, the radius of the surfel. One more recently developed method for constructing a three-dimensional map of the scene is the so-called “octree”. Octrees are a hierarchical data structure for a spatial representation of an object. Each octree node represents a space contained in a cubic volume called a voxel. This volume is recursively subdivided into eight sub-volumes until the specified minimum voxel size is reached. The minimum voxel size determines the resolution of the octree. Since octree is a hierarchical data structure, a tree can be reduced at any level to get a coarser spatial representation of the object. The decision on whether a given voxel is a busy object or not is made on the basis of a probabilistic approach. In the proposed paper we describe new efficient algorithm for surface reconstruction in three-dimensional space and with the help of computer simulation, the proposed method is compared with known algorithms for 3D map reconstruction.
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Dmitrii Tihonkih, Vitaly Kober, Artyom Makovetskii, and Aleksei Voronin "An efficient 3D mapping framework", Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372L (6 September 2019); https://doi.org/10.1117/12.2529632
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KEYWORDS
Clouds
3D modeling
Reconstruction algorithms
3D acquisition
Computer simulations
Robotics
Sensors
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