In this paper, we apply the collinearity constraint for accurate camera calibration and correction. The novel method consists of two steps: the first is to estimate the relative parameters of interest with closed form solutions. The second employs the well known Levernburg-Marquardt (LM) algorithm for the global optimization of all the parameters of interest: 4 intrinsic, 7 extrinsic and 4 distortion parameters. The LM algorithm is initialised either as the parameters estimated in the first step or as zero. The optimization is achieved through minimising the sum of the squared back projected errors. The distorted points are finally corrected using again the LM algorithm initialized by the distorted image points themselves, minimizing the squared difference between the distorted corrected point and the given distorted image point. A comparative study based on both synthetic data and real images show that the proposed algorithm produces promising camera calibration and correction results.
|Title of host publication||IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), 2009|
|Publication status||Published - 2009|
|Event||IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), 2009 - Daejeon, Korea (Republic of)|
Duration: 15 Dec 2009 → 18 Dec 2009
|Conference||IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), 2009|
|Country/Territory||Korea (Republic of)|
|Period||15 Dec 2009 → 18 Dec 2009|