Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Self-calibration of an affine camera from multiple views
International Journal of Computer Vision
Euclidean Shape and Motion from Multiple Perspective Views by Affine Iterations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Paraperspective Factorization Method for Shape and Motion Recovery
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sequential Updating of Projective and Affine Structure from Motion
International Journal of Computer Vision
A Unified Theory of Uncalibrated Stereo for Both Perspective and Affine Cameras
Journal of Mathematical Imaging and Vision
International Journal of Computer Vision - 1998 Marr Prize
Affine Structure and Motion from Points, Lines and Conics
International Journal of Computer Vision
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Epipolar Geometry in Stereo, Motion, and Object Recognition: A Unified Approach
Epipolar Geometry in Stereo, Motion, and Object Recognition: A Unified Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Structure from Many Perspective Images with Occlusions
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Euclidean Reconstruction from Uncalibrated Views
Proceedings of the Second Joint European - US Workshop on Applications of Invariance in Computer Vision
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Estimating 3D shape from degenerate sequences with missing data
Computer Vision and Image Understanding
An Iterative Multiresolution Scheme for SFM with Missing Data
Journal of Mathematical Imaging and Vision
An iterative multiresolution scheme for SFM with missing data: Single and multiple object scenes
Image and Vision Computing
The quasi-perspective model: Geometric properties and 3D reconstruction
Pattern Recognition
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We present a batch method for recovering Euclidian camera motion from sparse image data. The main purpose of the algorithm is to recover the motion parameters using as much of the available information and as few computational steps as possible. The algorithm thus places itself in the gap between factorisation schemes, which make use of all available information in the initial recovery step, and sequential approaches which are able to handle sparseness in the image data. Euclidian camera matrices are approximated via the affine camera model, thus making the recovery direct in the sense that no intermediate projective reconstruction is made. Using a little known closure constraint, the FA-closure, we are able to formulate the camera coefficients linearly in the entries of the affine fundamental matrices. The novelty of the presented work is twofold: Firstly the presented formulation allows for a particularly good conditioning of the estimation of the initial motion parameters but also for an unprecedented diversity in the choice of possible regularisation terms. Secondly, the new autocalibration scheme presented here is in practice guaranteed to yield a Least Squares Estimate of the calibration parameters.As a bi-product, the affine camera model is rehabilitated as a useful model for most cameras and scene configurations, e.g. wide angle lenses observing a scene at close range. Experiments on real and synthetic data demonstrate the ability to reconstruct scenes which are very problematic for previous structure from motion techniques due to local ambiguities and error accumulation.