Improved self-calibration algorithm of absolute dual quadric

Min Sun

doi:10.1117/12.747735

15 November 2007 Improved self-calibration algorithm of absolute dual quadric

Min Sun

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 67882L (2007) https://doi.org/10.1117/12.747735
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Camera self-calibration is one key problem in 3D reconstruction from image sequences. In this paper, a further discussion is given for self-calibration method of Absolute Dual Quadric (ADQ). This method using projective matrix as known data to extract camera intrinsic parameters, however, projective matrix still contains some uncertain variables, and optimization to them were ignored, in addition, the utilities of constraint conditions are not convincible in nonlinear algorithm of this method. An improved algorithm is given to resolve these problems in this paper. The main idea of the improved algorithm is to recalculate projective matrix with middle calibration result in each iterative process of the algorithm, and set convergence of iterative process to the point on parabolas where the ratio of initial focal length to its result reach to 1.0. Experiment result from real image data shows that improved algorithm is efficient.

Citation Download Citation

Min Sun "Improved self-calibration algorithm of absolute dual quadric", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67882L (15 November 2007); https://doi.org/10.1117/12.747735

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KEYWORDS

Calibration

Cameras

3D modeling

Clouds

3D image processing

3D image reconstruction

Polishing

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