Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Characterizing the uncertainty of the fundamental matrix
Computer Vision and Image Understanding
3-D reconstruction of urban scenes from image sequences
Computer Vision and Image Understanding - Special issue on CAD-based computer vision
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
Stereo Calibration from Rigid Motions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Singular Displacements for Uncalibrated Monocular Visual Systems
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Reliable Extraction of the Camera Motion using Constraints on the Epipole
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
An integrated stereo-based approach to automatic vehicle guidance
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
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This paper presents a method of autocalibrating a stereo system using the full parameterization of the fundamental matrix. The technique is an improvement of classical autocalibration methods that use corresponding points and it is aimed to reduce the number of processes required to achieve a satisfactory calibration. An analysis of the matching points used in the calibration process is carried out in order to select them based upon their quality or reliability. Using this technique, a significant reduction of the convergence errors in the calibration process is obtained.