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- W2387673755 abstract "Based on 2D pattern,different nonlinear optimization algorithms are used to calibrate the camera parameters including the linear parameters and distortions.Two basic restrictions are deduced from the characteristics of homography based on image of the absolute conic.By establishing the corresponding relationship between elements in IAC matrix and intrinsic parameters,the initial values of intrinsic parameters are solved linearly while the initial extrinsic parameters are obtained through the relationship between homography and linear parameters.By analyzing radial and tangential distortions and using Rodrigues' rotation formula to decrease the number of optimization parameters,two optimiztion algorithms,namely the steepest descent algorithm and the Levenberg-Marquad algorithm are used to obtain the accurate parameters.The results show that nonlinear optimization algorithms for camera calibration based on 2D pattern can simplify the calculation of initial parameter and steepest descent algorithm while Levenberg-Marquad algorithm obtains projection with smaller errors.The latter can be performed with optimization toolbox to reduce the calculation difficulty obviously.Optimization algorithms should be chosen depending on practical conditions to obtain accurate the camera parameters quickly." @default.
- W2387673755 created "2016-06-24" @default.
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- W2387673755 date "2013-01-01" @default.
- W2387673755 modified "2023-10-12" @default.
- W2387673755 title "Nonlinear optimization algorithms for camera calibration based on 2D pattern" @default.
- W2387673755 hasPublicationYear "2013" @default.
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