Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2003-07-20
Computer Science
Computer Vision and Pattern Recognition
6 pages, 2 Postscript figures
Scientific paper
Most algorithms in 3D computer vision rely on the pinhole camera model because of its simplicity, whereas virtually all imaging devices introduce certain amount of nonlinear distortion, where the radial distortion is the most severe part. Common approach to radial distortion is by the means of polynomial approximation, which introduces distortion-specific parameters into the camera model and requires estimation of these distortion parameters. The task of estimating radial distortion is to find a radial distortion model that allows easy undistortion as well as satisfactory accuracy. This paper presents a new radial distortion model with an easy analytical undistortion formula, which also belongs to the polynomial approximation category. Experimental results are presented to show that with this radial distortion model, satisfactory accuracy is achieved. An application of the new radial distortion model is non-iterative yellow line alignment with a calibrated camera on ODIS, a robot built in our CSOIS.
Chen YangQuan
Ma Lili
Moore Kevin L.
No associations
LandOfFree
Flexible Camera Calibration Using a New Analytical Radial Undistortion Formula with Application to Mobile Robot Localization does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Flexible Camera Calibration Using a New Analytical Radial Undistortion Formula with Application to Mobile Robot Localization, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Flexible Camera Calibration Using a New Analytical Radial Undistortion Formula with Application to Mobile Robot Localization will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-17009