A theory of self-calibration of a moving camera
International Journal of Computer Vision
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
In defence of the 8-point algorithm
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Estimation with Bilinear Constraints in Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
From Projective to Euclidean Space Under any Practical Situation, a Criticism of Self-Calibration
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Depth recovery and affine reconstruction under camera pure translation
Pattern Recognition
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We present a technique for camera calibration and Euclidean reconstruction from multiple images of the same scene. Unlike standard Tsai's camera calibration from a known scene, we exploited controlled known motions of the camera to obtain its calibration and Euclidean reconstruction without any knowledge about the scene. We consider three linearly independent translations of an uncalibrated camera mounted on a robot arm that provides us with four views of the scene. The translations of the robot arm are measured in a robot coordinate system. This special, but still realistic, arrangement allowed us to find a linear algorithm for recovering all intrinsic camera calibration parameters, the rotation of the camera with respect to the robot coordinate system, and proper scaling factors for all points allowing their Euclidean reconstruction. The experiments showed that an efficient and robust algorithm was obtained by exploiting Total Least Squares in combination with careful normalization of image coordinates.