Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Linear subspace methods for recovering translational direction
Proceedings of the 1991 York conference on Spacial vision in humans and robots
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Unified Approach to Moving Object Detection in 2D and 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multi-Frame Structure-from-Motion Algorithm under Perspective Projection
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
Extracting Structure from Optical Flow Using the Fast Error Search Technique
International Journal of Computer Vision
A critique of structure-from-motion algorithms
Computer Vision and Image Understanding
A New Structure-from-Motion Ambiguity
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Factorization Based Algorithm for Multi-Image Projective Structure and Motion
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Recursive Structure and Motion from Image Sequences using Shape and Depth Spaces
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Structure from Linear or Planar Motions
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Factorization Methods for Projective Structure and Motion
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Computing the Camera Heading from Multiple Frames
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Multiframe structure from motion in perspective
VSR '95 Proceedings of the IEEE Workshop on Representation of Visual Scenes
Removal of Translation Bias when Using Subspace Methods
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Fast and Accurate Self-Calibration
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
New Algorithms for Two-Frame Structure from Motion
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Direct Multi-Frame Structure from Motion for Hand-Held Cameras
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Factorization with Uncertainty
International Journal of Computer Vision
Exact Two-Image Structure from Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure from Planar Motions with Small Baselines
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Stochastic Approximation and Rate-Distortion Analysis for Robust Structure and Motion Estimation
International Journal of Computer Vision
International Journal of Computer Vision
The least-squares error for structure from infinitesimal motion
International Journal of Computer Vision
Motion and Shape Recovery Based on Iterative Stabilization for Modest Deviation from Planar Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iterative Extensions of the Sturm/Triggs Algorithm: Convergence and Nonconvergence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiframe Motion Segmentation with Missing Data Using PowerFactorization and GPCA
International Journal of Computer Vision
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We describe algorithms for computing projective structure and motion from a multi-image sequence of tracked points. The algorithms are essentially linear, work for any motion of moderate size, and give accuracies similar to those of a maximum-likelihood estimate. They give better results than the Sturm/Triggs factorization approach and are equally fast and they are much faster than bundle adjustment. Our experiments show that the (iterated) Sturm/Triggs approach often fails for linear camera motions. In addition, we study experimentally the common situation where the calibration is fixed and approximately known, comparing the projective versions of our algorithms to mixed projective/Euclidean strategies. We clarify the nature of dominant-plane compensation, showing that it can be considered a small-translation approximation rather than an approximation that the scene is planar. We show that projective algorithms accurately recover the (projected) inverse depths and homographies despite the possibility of transforming the structure and motion by a projective transformation.