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Methods of 3D object model creation on the basis of unstructured (sparse) cloud of points are considered in the paper. The issues of combining point cloud compaction methods and subsequent surface generation are described. The comparative analysis of generation surfaces algorithms for the purpose of revealing of more effective method using as input data the depth maps received from the sparse cloud of points is carried out. The comparison is made by qualitative, quantitative and temporal criteria. The optimal method of 3D object model creation on the basis of unstructured (sparse) cloud of points and depth map data is chosen. The mathematical description of the point cloud compaction method on the basis of stereo-matching with application of two-phase algorithm of species search and depth map extraction from Multi-View Stereo for Community Photo Collections source image set is provided. The implementation of the method in open-source software Regard3D is realized in practice.

Investigation of Algorithms for Generating Surfaces of 3D Models Based on an Unstructured Point Cloud