Recognition and 3D-reconstruction of objects from images using a priori information

Author

Zakharov, A.A. ; Zhiznyakov, A.L.

Author_Institution

Murom Inst. (branch), Vladimir State Univ. named after Alexander G. & Nikolay G. Stoletovs, Vladimir, Russia

fYear

2014

fDate

7-13 Sept. 2014

Firstpage

368

Lastpage

369

Abstract

The probabilistic approach of three-dimensional reconstruction of the visual environment of urban scenes from satellite and aerial images is presented. The mathematical model of the reconstructed objects is presented. Contour images of models of reconstructed objects are shown. Conditional probability of occurrence of recognizable signs and reconstructed objects are used in the model. Hough transform is used for feature extraction. The approach aim is to find maximum a posteriori probability of the synthesized model. A maximum a posteriori probability is using Monte Carlo Markov chain scheme. Possible transitions between the models for the iterative search are presented in the paper.

Keywords

Markov processes; Monte Carlo methods; feature extraction; image reconstruction; maximum likelihood estimation; object recognition; probability; 3D-reconstruction; Hough transform; Monte Carlo Markov chain scheme; conditional probability approach; feature extraction; iterative search; mathematical model; maximum a posteriori probability; object recognition; three-dimensional reconstruction; urban scenes; Image recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Microwave & Telecommunication Technology (CriMiCo), 2014 24th International Crimean Conference

Conference_Location

Sevastopol

Print_ISBN

978-966-335-412-5

Type

conf

DOI

10.1109/CRMICO.2014.6959436

Filename

6959436