Hierarchical structure-and-motion recovery from uncalibrated images
arXiv:1506.00395 · doi:10.1016/j.cviu.2015.05.011
Abstract
This paper addresses the structure-and-motion problem, that requires to find camera motion and 3D struc- ture from point matches. A new pipeline, dubbed Samantha, is presented, that departs from the prevailing sequential paradigm and embraces instead a hierarchical approach. This method has several advantages, like a provably lower computational complexity, which is necessary to achieve true scalability, and better error containment, leading to more stability and less drift. Moreover, a practical autocalibration procedure allows to process images without ancillary information. Experiments with real data assess the accuracy and the computational efficiency of the method.
Accepted for publication in CVIU
Cited by in corpus (7)
- Spectral Motion Synchronization in SE(3)
- Parallel Structure from Motion from Local Increment to Global Averaging
- Parallel Structure from Motion for UAV Images via Weighted Connected Dominating Set
- CSfM: Community-based Structure from Motion
- Robust SfM with Little Image Overlap
- Graph-Based Parallel Large Scale Structure from Motion
- Pointless Global Bundle Adjustment With Relative Motions Hessians