Structure from Motion Causally Integrated Over Time
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Non-linear Optimization of Projective Motion Using Minimal Parameters
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
3-D Motion and Structure from 2-D Motion Causally Integrated over Time: Implementation
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Gauge Independence in Optimization Algorithms for 3D Vision
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Nonlinear Estimation of the Fundamental Matrix with Minimal Parameters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneous and Sequential Reconstruction of Visual Primitives with Bundle Adjustment
Journal of Mathematical Imaging and Vision
Scene point constraints in camera auto-calibration: an implementational perspective
Image and Vision Computing
Projective reconstruction of all visual primitives
Pattern Recognition
Visual-inertial navigation, mapping and localization: A scalable real-time causal approach
International Journal of Robotics Research
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Bundle adjustment is a standard photogrammetric technique for optimizing the 3D reconstruction of a scene from multiple images. There is an inherent gauge (coordinate frame) ambiguity in 3D reconstruction that can seriously affect the convergence of bundle adjustment algorithms. We address this issue and show that a simple preconditioning step removes the effect of the choice of coordinate frame, and together with a set of enforced constraints on the reconstruction, achieves along with this invariance greatly increased convergence speed over existing methods. The new approach applies to all the well-known 3D reconstruction models: projective, affine and Euclidean. In this paper we develop the idea for projective reconstruction.The normalization stage partially removes the gauge freedom, reducing the coordinate frame choice from a general 3D homography to an orthogonal transformation; then constraints are incorporated in the bundle adjustment iterations that enforce the normalisation condition to first order. In the projective case the approach relies on a currently unproven matrix conjecture, which we nevertheless strongly believe to be correct, based on extensive experimental evidence.