In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Do We Really Need an Accurate Calibration Pattern to Achieve a Reliable Camera Calibration?
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Machine Vision and Applications
Nonmetric calibration of camera lens distortion: differential methods and robust estimation
IEEE Transactions on Image Processing
Research on Parts Measurement Method Based on Machine Vision
International Journal of Advanced Pervasive and Ubiquitous Computing
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Camera calibration is necessary to obtain 3D information from 2D images of a scene. Different techniques exist which are based on photo-grammetry or self-calibration. As a result of the calibration the intrinsic and extrinsic camera parameters are computed. A lot of work has been done in camera calibration and also in data pre- and post-processing techniques. From a practical point of view, it is quite difficult to decide which calibration method produces the best results and even whether any data processing at all is necessary.This paper defines the best performance camera calibration algorithm. Based on the state of the art of all camera calibration processes, including pre- and post-processing data, a camera calibration method is chosen on the grounds of robustness and ease of handing. After, the calibration method is improved adding pre- and post-processing statements. Data treatment reduces the noise of the measurements and optimum performance is thus achieved. Its performance is tested with both simulated and real data and best results are always computed. The aim is to define a complete method which will allow all camera calibration situations to be easily resolved.