Using vanishing points for camera calibration
International Journal of Computer Vision
Relative motion and pose from arbitrary plane curves
Image and Vision Computing
Camera calibration from spheres images
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Camera Calibration from Surfaces of Revolution
IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera Calibration with One-Dimensional Objects
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Circular Motion Geometry by Minimal 2 Points in 4 Images
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Camera calibration using spheres: A semi-definite programming approach
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 4 - Volume 04
A Desktop 3D Scanner Exploiting Rotation and Visual Rectification of Laser Profiles
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Full Camera Calibration from a Single View of Planar Scene
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Shape reconstruction and texture sampling by active rectification and virtual view synthesis
Computer Vision and Image Understanding
Integrating multiple views with virtual mirrors to facilitate scene understanding
ACM Transactions on Applied Perception (TAP)
Precise 3d reconstruction from a single image
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
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We present an approach for camera calibration from the image of at least two circles arranged in a coaxial way. Such a geometric configuration arises in static scenes of objects with rotational symmetry or in scenes including generic objects undergoing rotational motion around a fixed axis. The approach is based on the automatic localization of a surface of revolution (SOR) in the image, and its use as a calibration artifact. The SOR can either be a real object in a static scene, or a “virtual surface” obtained by frame superposition in a rotational sequence. This provides a unified framework for calibration from single images of SORs or from turntable sequences. Both the internal and external calibration parameters (square pixels model) are obtained from two or more imaged cross sections of the SOR, whose apparent contour is also exploited to obtain a better calibration accuracy. Experimental results show that this calibration approach is accurate enough for several vision applications, encompassing 3D realistic model acquisition from single images, and desktop 3D object scanning.