Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Automatic Model Construction and Pose Estimation From Photographs Using Triangular Splines
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Epipolar Geometry from Profiles under Circular Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-Calibration from Image Triplets
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Object Models from Contour Sequences
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Automatic Camera Recovery for Closed or Open Image Sequences
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Single Axis Geometry by Fitting Conics
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Factorization Methods for Projective Structure and Motion
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Multiple Motion Scene Reconstruction with Uncalibrated Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Resolving Ambiguities of Self-Calibration in Turntable Motion
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Circular Motion Geometry Using Minimal Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In this paper, we propose a new method for 3D reconstruction from an image sequence captured by a camera with constant intrinsic parameters undergoing circular motion. We introduce a method, called circular projective reconstruction, for enforcing the circular constraint in a factorization-based projective reconstruction. To deal with the missing data problem, our method uses a multi-stage approach to reconstructing the objects and cameras, which first computes a circular projective reconstruction of a sub-sequence and then extends the reconstruction to the complete sequence. Camera matrix, rotation angles, and 3D structure are computed iteratively in a way that the 2D reprojection error is minimized. The algorithm is evaluated using real image sequences.