Motion and Structure From Two Perspective Views: Algorithms, Error Analysis, and Error Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric invariance in computer vision
Geometric invariance in computer vision
Canonic representations for the geometries of multiple projective views
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Towards a General Multi-View Registration Technique
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matrix computations (3rd ed.)
Sequential Updating of Projective and Affine Structure from Motion
International Journal of Computer Vision
Affine Structure from Line Correspondences With Uncalibrated Affine Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Framework for Uncertainty and Validation of 3-D RegistrationMethods Based on Points and Frames
International Journal of Computer Vision
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure and Motion from Line Segments in Multiple Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Camera Recovery for Closed or Open Image Sequences
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Uncertainty Modeling for Optimal Structure from Motion
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Gauge Invariance in Projective 3D Reconstruction
MVIEW '99 Proceedings of the IEEE Workshop on Multi-View Modeling & Analysis of Visual Scenes
Quasi-Dense Reconstruction from Image Sequence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Estimating the mutual orientation in a multi-camera system with a non overlapping field of view
PIA'11 Proceedings of the 2011 ISPRS conference on Photogrammetric image analysis
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We attack the problem of coordinate frame dependence and gauge freedoms in structure-from-motion. We are able to formulate a bundle adjustment algorithm whose results are independent of both the coordinate frame chosen to represent the scene and the ordering of the images. This method is more efficient that existing approaches to the problem in photogrammetry. We demonstrate that to achieve coordinate frame independent results, (i) Rotations should be represented by quaternions or local rotation parameters, not angles, and (ii) the translation vector describing the camera/ scene motion should be represented in scene 3D coordinates, not camera 3D coordinates, two representations which are normally treated as interchangeable. The algorithm allows 3D point and line features to be reconstructed. Implementation is via the efficient recursive partitioning algorithm common in photogrammetry. Results are presented demonstrating the advantages of the new method in terms of the stability of the bundle adjustment iterations.