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A fast and accurate iterative method for the camera pose estimation problem
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DOI：10.1016/j.imavis.2019.103860.png)
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This paper presents a fast and accurate iterative method for camera pose estimation problem. The dependence on initial values is reduced by replacing unknown angular parameters with three independent non-angular parameters. Image point coordinates are treated as observations with errors and a new model is built using a conditional adjustment with parameters for relative orientation. This model allows for the estimation of the errors in the observations. The estimated observation errors are then used iteratively to detect and eliminate gross errors in the adjustment. A total of 22 synthetic datasets and 10 real datasets are used to compare the proposed method with the traditional iterative method, the 5-point-RANSAC and the state-of-the-art 5-point-USAC methods. Preliminary results show that our proposed method is not only faster than the other methods, but also more accurate and stable. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Camera pose estimation
Direct relative orientation
Iterative method
Parameterization
Gross detection and elimination
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