METHODS FOR MODELS PARAMETERS ESTIMATE TO SOLVE PROBLEMS ON 3D RECONSTRUCTION OF REAL OBJECTS COMPLEX MODELS
Abstract and keywords
Abstract (English):
Virtual threedimensional (3 D) models of complex objects are used in many fields of science and engineering, such as architecture, industry, medicine, robotics. Besides, 3D models are used in geoinformation systems, computer games, virtual and supplemented reality and so on. Three dimensional models can be formed in dif-ferent ways, one of which consists in 3 D reconstruc-tion. One of the stages of the 3 D reconstruction of complex models of real objects is a definition of the mathematical models of geometric primitives emphasized on the image. One of the ways for the estimate of model parameters is a method of Hough vote and its modifications – Hough probabilistic transformation, Hough random transformation, Hough hierarchical transformation, phase space blurriness, use of a gra-dient of image brightness and so on. As an alternative way for models selection is a choice of suitable points from a set of data.

Keywords:
characteristic points, models parameters, Hough vote method, M-estimate function, outputs on images, leastsquares method, RANSAC, AVLESAC, MLESAC, M – SAC, MAPSAC, R – RANSAC, ARSAC
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