Sciweavers

Share
ICCV
2007
IEEE

Out-of-Core Bundle Adjustment for Large-Scale 3D Reconstruction

9 years 7 months ago
Out-of-Core Bundle Adjustment for Large-Scale 3D Reconstruction
Large-scale 3D reconstruction has recently received much attention from the computer vision community. Bundle adjustment is a key component of 3D reconstruction problems. However, traditional bundle adjustment algorithms require a considerable amount of memory and computational resources. In this paper, we present an extremely efficient, inherently out-of-core bundle adjustment algorithm. We decouple the original problem into several submaps that have their own local coordinate systems and can be optimized in parallel. A key contribution to our algorithm is making as much progress towards optimizing the global non-linear cost function as possible using the fragments of the reconstruction that are currently in core memory. This allows us to converge with very few global sweeps (often only two) through the entire reconstruction. We present experimental results on large-scale 3D reconstruction datasets, both synthetic and real.
Kai Ni, Drew Steedly, Frank Dellaert
Added 14 Oct 2009
Updated 30 Oct 2009
Type Conference
Year 2007
Where ICCV
Authors Kai Ni, Drew Steedly, Frank Dellaert
Comments (0)
books