Self-calibration from multiple views with a rotating camera
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications
Self-Calibration from Image Triplets
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Stratified Self Calibration from Screw-Transform Manifolds
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Stereo Autocalibration from One Plane
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Critical Motion Sequences for Monocular Self-Calibration and Uncalibrated Euclidean Reconstruction
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
The Modulus Constraint: A New Constraint for Self-Calibration
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Camera Autocalibration and Horopter Curves
International Journal of Computer Vision
Camera Self-Calibration: A New Approach for Solving the Modulus Constraint
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
A New Linear Method for Camera Self-Calibration with Planar Motion
Journal of Mathematical Imaging and Vision
Linear auto-calibration for ground plane motion
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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We present a closed-form method for the self-calibration of a camera (intrinsic and extrinsic parameters) from at least three images acquired with parallel screw axis motion, i.e. the camera rotates about parallel axes while performing general translations. The considered camera motion is more general than pure rotation and planar motion, which are not always easy to produce. The proposed solution is nearly as simple as the existing for those motions, and it has been evaluated by using both synthetic and real data from acquired images.