Proceedings Article10.1109/ICIG.2011.97
Graph Partition Based Bundle Adjustment for Structured Dataset
Yuanfan Xie,Lixin Fan,Yihong Wu +2 more
- 12 Aug 2011
- pp 1010-1016
TL;DR: A sub mapping method, which partitions a large scale dataset into disjointed subsets and adjusts them one by one or in parallel and "stitched" together by applying a similarity transformation, which scales well.
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Abstract: Bundle adjustment has been considered as one of the most important components in many visual tasks such as 3D reconstruction, photo grammetry, visual SLAM, etc. Unfortunately, both time and space complexity of this adjustment prevent it from being directly applied to large scale datasets. This paper presents a sub mapping method, which partitions a large scale dataset into disjointed subsets and adjusts them one by one or in parallel. Pair-wise sub maps are then "stitched" together by applying a similarity transformation. Both simulations and real applications show that our method scales well. Also some basic questions of this sub mapping method including map size, map fusion and global consistency are discussed.
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Citations
A Novel Algorithm for Ship Detection Based on Dynamic Fusion Model of Multi-feature and Support Vector Machine
Yu Xia,Shouhong Wan,Lihua Yue +2 more
- 12 Aug 2011
TL;DR: This paper proposes an uncertain ship target extraction algorithm based on dynamic fusion model of multi-feature and variance feature of optical remote sensing image, using SVM to train and predict the uncertain ship targets extracted by the algorithm automatically.
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Bundle Adjustment - A Modern Synthesis
Bill Triggs,Philip F. McLauchlan,Richard Hartley,Andrew Fitzgibbon +3 more
- 21 Sep 1999
TL;DR: A survey of the theory and methods of photogrammetric bundle adjustment can be found in this article, with a focus on general robust cost functions rather than restricting attention to traditional nonlinear least squares.
Building Rome in a day
Sameer Agarwal,Noah Snavely,Ian Simon,Steven M. Seitz,Richard Szeliski +4 more
- 01 Sep 2009
TL;DR: A system that can match and reconstruct 3D scenes from extremely large collections of photographs such as those found by searching for a given city on Internet photo sharing sites and is designed to scale gracefully with both the size of the problem and the amount of available computation.
SBA: A software package for generic sparse bundle adjustment
TL;DR: Sba as mentioned in this paper is a C/C++ software package for generic bundle adjustment with high efficiency and flexibility regarding parameterization, which can be used to achieve considerable computational savings when applied to bundle adjustment.
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