Self-Calibration of Stationary Cameras
International Journal of Computer Vision
A comparison of projective reconstruction methods for pairs of views
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
On the determination of Epipoles using cross-ratios
Computer Vision and Image Understanding
Statistical Optimization for Geometric Computation: Theory and Practice
Statistical Optimization for Geometric Computation: Theory and Practice
Camera Self-Calibration: Theory and Experiments
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Autocalibration and the absolute quadric
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A unifying framework for structure and motion recovery from image sequences
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Euclidean Reconstruction from Constant Intrinsic Parameters
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Projective Structure from two Uncalibrated Images: Structure from Motion and Recognition
Projective Structure from two Uncalibrated Images: Structure from Motion and Recognition
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The Robotic systems for disabled people, aims at bringing a piloting assistance to powered wheelchairs in answer to the needs of mobility aid using dynamic vision techniques from mobile robotics. People start to design the robot with the fastest computers to process the information, together with high quality camera to serve as its eye, and precise mechanical motion control. The main working mode for this purpose is a contribution to dynamic vision, in the aim to improve a visio-space behavior of handicapped children. A self-calibration technique of a visual sensor is described: self-calibration implying the adoption of methods allowing to calibrate automatically a camera without using of special calibration set-ups. This paper examines what can be done within a Euclidean calibration, when the internal parameters must remain constant any more. So, we look at a Euclidean basis being a projective and one where some constraints must be observed. This work shows theoretically along with real experiments, how it is possible to completely calibrate a camera in line, that is to determine the intrinsic parameters and the relative displacement between two or three images, without any a priori knowledge of the scenes. The infinite homography computing method is used to estimate intrinsic and extrinsic parameters. This procedure consists of a closed-form solution, followed by a nonlinear refinement based on a bundle adjustment criterion.