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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References

1. Ivanov, V.P. 3D Computer Graphics / V.P. Ivanov, А.S. Batrakov; under the editorship of G.М. Polish-chuk. – М., 2011. – pp. 224.

2. Dragomirov, D. Yu. 3D computer reconstruction of architecture monuments / D.Yu. Dragomirov // Bul-letin of UdmSU. –2006. – №12.

3. Lee, J. 3D Graphics and Animation / J. Lee, B. Wer. – 2-d Ed. –М.: Williams, 2002. – pp. 640.

4. Davies, E. R. Machine Vision : Theory, Algorithms, Practicalities/ E. R. Davies. – Morgan Kaufmann, 2004.

5. Forsyth, D.A. Computer Vision: A Modern Approach / D.A. Forsyth, J. Ponce. - 2ed. - 2012. – 792 p.

6. P.V.C. Hough, A method and means for recognizing complex patterns: US patente 3069654. – 1962.

7. Degtyaryova, А. Hough transform / А. Degtyaryova, V. Verzhnevets//Computer Graphics and Mul-timedia. – 2003. – Issue. №1(2).

8. Hartley, R. Multiple View Geometry in Computer Vision / R. Hartley, A. Zisserman. – 2d. – Cambridge University Press, 2003.

9. Fischler, M. A. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography / M.A. Fischler, R.C. Bolles // Comm. Of the ACM 24. – 1981. – Р. 381–395.

10. Chum, О. Two-View Geometry Estimation by Random Sample and Consensus / O. Chum // PhD Thesis. – 2005.

11. Huber, P.J. Robust Statistics / P.J. Huber. – John Wiley and Sons, 1981.

12. Choi, S. Performance Evaluation of RANSAC Family / S. Choi, T. Kim, W. Yu. – 2009.

13. Capel, D. An effective bailout test for RANSAC consensus scoring / D. Capel // In Proceedings of the British Machine Vision Conference (BMVC). - 2005.

14. Choi, S. Robust regression to varying data distribution and its application to landmarkbased localization / S. Choi, Jong-Hwan Kim // In Proceedings of the IEEE Conference on Systems, Man and Cyber-netics. - 2008.

15. 15.Chum, O. Randomized RANSAC with Td,d test. / O. Chum, JMatas // In Proceedings of the 13th British Machine Vision Conference (BMVC). – 2002. – Р. 448–457.

16. Konushin, А. Review of robust schemes of models parameters estimate based on random samplings / А.Konushin, К. Marinichev, V. Verzhnevets // Proceedings of the Conf. GraphiCon-2004. — 2004. — pp. 275–278.

17. Zhuk, D.V. 3D model reconstruction on two digital images / D.V. Zhuk, А. V. Tuzikov // Informatics.– 2006. –№ 1. – pp. 16–26.

18. Veksler, O. Stereo correspondence by dynamic programming on a tree / O. Veksler // Proc. CVPR. – 2005. –Vol. 2. – P. 384–390.

19. Rusinkiewicz, S. QSplat: a multiresolution point rendering system for large meshes / S.Rusinkiewicz, M.Levoy //In Siggraph ACM. - New York,. – 2000. – Р. 343-352.

20. Konouchine, A. AMLESAC: A New Maximum Likelihood Robust Estimator / A.Konouchine, V.Gaganov, V.Veznevets // Graphicon 2005 pro-ceedings.

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