Evolutionary Approach to Epipolar Geometry Estimation

Taraglio, Sergio; Chiesa, Stefano Della

doi:10.5772/13040

Cited by 3 publications

(3 citation statements)

References 16 publications

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“…Even for low detailed images which have a small number of matched points available to estimate the fundamental matrix, the proposed GA outperformed other methods like the eight-points GA 3 and GeneticAlgo. 18 The proposed technique satis¯es the rank-2 constraint which means that the epipolar geometry will be properly modeled.…”

Section: Resultsmentioning

confidence: 99%

“…In Ref. 18, a set of solutions for the epipolar geometry estimation is hypothesize, tested against the available matching points, and then genetically optimized against a¯tness function computed over the correspondences set. Each individual is implicitly a possible fundamental matrix and is implemented by a vector of six real values representing the chromosomes: ii ¼ ½; '; ; t ; t ; ], these chromosomes are the three angles of a three-dimensional rotation (the pitch, roll and yaw angles), two direction cosines for the translation and a sixth value that is the standard deviation of a normal distribution used for the chromosome mutation.…”

Section: Related Workmentioning

confidence: 99%

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A Ga-Based Approach for Epipolar Geometry Estimation

Khaled

Hemayed

Fayek

2013

Int. J. Patt. Recogn. Artif. Intell.

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In this paper, a genetic algorithm (GA)-based approach to estimate the fundamental matrix is presented. The aim of the proposed GA-based algorithm is to reduce the e®ect of noise and outliers in the corresponding points which a®ect the accuracy of the estimated fundamental matrix. Although in the proposed approach the GA is allowed to select the signi¯cant among all detected points, on the average half of the matched points have been determined to give optimum estimation of the fundamental matrix. Experiments with synthetic and real data show that the proposed approach is accurate especially in the presence of a high percentage of outliers. The proposed GA can always obtain good results in both high and low detailed images. Even for low detailed images which have a small number of matched points available to estimate the fundamental matrix, the proposed GA outperformed other methods.

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Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A Ga-Based Approach for Epipolar Geometry Estimation

Khaled

Hemayed

Fayek

2013

Int. J. Patt. Recogn. Artif. Intell.

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“…To overcome this drawback, the search space can be re-parameterized as a rotation space. Taraglio and Chiesa (2011) propose a genetic approach for estimating the epipolar geometry by directly searching the space of five relative orientation parameters. However, the continuous, 5-dimensional search-space reduces the chance of reaching the optimal solution with evolutionary search, specifically when high accuracy is required.…”

Section: Inlier Detection Based On Epipolar Geometrymentioning

confidence: 99%

Robust Sparse Matching and Motion Estimation Using Genetic Algorithms

Shahbazi

Sohn

Théau

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In this paper, we propose a robust technique using genetic algorithm for detecting inliers and estimating accurate motion parameters from putative correspondences containing any percentage of outliers. The proposed technique aims to increase computational efficiency and modelling accuracy in comparison with the state-of-the-art via the following contributions: i) guided generation of initial populations for both avoiding degenerate solutions and increasing the rate of useful hypotheses, ii) replacing random search with evolutionary search, iii) possibility of evaluating the individuals of every population by parallel computation, iv) being performable on images with unknown internal orientation parameters, iv) estimating the motion model via detecting a minimum, however more than enough, set of inliers, v) ensuring the robustness of the motion model against outliers, degeneracy and poorperspective camera models, vi) making no assumptions about the probability distribution of inliers and/or outliers residuals from the estimated motion model, vii) detecting all the inliers by setting the threshold on their residuals adaptively with regard to the uncertainty of the estimated motion model and the position of the matches. The proposed method was evaluated both on synthetic data and real images. The results were compared with the most popular techniques from the state-of-the-art, including RANSAC, MSAC, MLESAC, Least Trimmed Squares and Least Median of Squares. Experimental results proved that the proposed approach perform better than others in terms of accuracy of motion estimation, accuracy of inlier detection and the computational efficiency.

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Fusion of three techniques for person detection in real time

Boukamcha

Atri

2014

2014 World Congress on Computer Applications and Information Systems (WCCAIS)

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Evolutionary Approach to Epipolar Geometry Estimation

Cited by 3 publications

References 16 publications

A Ga-Based Approach for Epipolar Geometry Estimation

A Ga-Based Approach for Epipolar Geometry Estimation

Robust Sparse Matching and Motion Estimation Using Genetic Algorithms

Fusion of three techniques for person detection in real time

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