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Robust camera parameter estimation using genetic algorithm
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DOI：10.1016/S0167-8655(00)00125-2.png)
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In this paper. we propose a genetic algorithm (GA)-based approach to determine the external parameters of the camera from the knowledge of a given set of points in object space. We study the effect of noise and presence of outliers, and also mismatch resulting from incorrect correspondences between the object space points and the image space points, on the estimation of three translation parameters and three rotational parameters of a camera. The average of the magnitudes of the translation errors varies from 2.25 cm to 5 mm and the average of the magnitudes of the rotational errors varies from 0.4 degrees to 0.25 degrees at 20 dB SNR. The error in parameter estimation is insignificant upto three pairs of mismatched points out of 20 points in object space and skyrockets when four or more pairs of points are mismatched. These results have clearly established the robustness of GA in external camera parameter estimation. (C) 2001 Elsevier Science B.V. All rights reserved.
Keyword:
camera calibration
pose estimation
genetic algorithm (ANN)
robust estimator
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3.3
论文数:
7.9K
被引数:
1.6W
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