Computer Vision and Image Understanding
Real-Time Epipolar Geometry Estimation of Binocular Stereo Heads
IEEE Transactions on Pattern Analysis and Machine Intelligence
Three D-Dynamic Scene Analysis: A Stereo Based Approach
Three D-Dynamic Scene Analysis: A Stereo Based Approach
Real-Time Correlation-Based Stereo Vision with Reduced Border Errors
International Journal of Computer Vision
Algebraic Functions For Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Weighting and Choosing Constraints for Optimally Reconstructing the Geometry of Image Triplets
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
A linear method for reconstruction from lines and points
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Continuous stereo self-calibration by camera parameter tracking
IEEE Transactions on Image Processing
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This contribution presents an approach for the continuous self-calibration of an active stereo rig with verging cameras. The proposed self-calibration recovers extrinsic parameters up to scale as well as the focal lengths of both cameras. Three different categories of constraint equations are evaluated and formulated as a Gauss-Helmert model for self-calibration: bundle adjustment with reduced parameter vector, the epipolar constraint, and the trilinear constraints. The optimization of the constraints is implemented as a robust Iterated Extended Kalman Filter that allows initial stereo calibration as well as continuous tracking of the camera parameters. The performance of the algorithm is demonstrated on synthetic and real imagery.