Resection-Intersection Bundle Adjustment Revisited. (12th December 2013)
- Record Type:
- Journal Article
- Title:
- Resection-Intersection Bundle Adjustment Revisited. (12th December 2013)
- Main Title:
- Resection-Intersection Bundle Adjustment Revisited
- Authors:
- Lakemond, Ruan
Fookes, Clinton
Sridharan, Sridha - Other Names:
- Gasteratos A. Academic Editor.
Pardàs M. Academic Editor. - Abstract:
- Abstract : Bundle adjustment is one of the essential components of the computer vision toolbox. This paper revisits the resection-intersection approach, which has previously been shown to have inferior convergence properties. Modifications are proposed that greatly improve the performance of this method, resulting in a fast and accurate approach. Firstly, a linear triangulation step is added to the intersection stage, yielding higher accuracy and improved convergence rate. Secondly, the effect of parameter updates is tracked in order to reduce wasteful computation; only variables coupled to significantly changing variables are updated. This leads to significant improvements in computation time, at the cost of a small, controllable increase in error. Loop closures are handled effectively without the need for additional network modelling. The proposed approach is shown experimentally to yield comparable accuracy to a full sparse bundle adjustment (20% error increase) while computation time scales much better with the number of variables. Experiments on a progressive reconstruction system show the proposed method to be more efficient by a factor of 65 to 177, and 4.5 times more accurate (increasing over time) than a localised sparse bundle adjustment approach.
- Is Part Of:
- ISRN machine vision. Volume 2013(2013)
- Journal:
- ISRN machine vision
- Issue:
- Volume 2013(2013)
- Issue Display:
- Volume 2013, Issue 2013 (2013)
- Year:
- 2013
- Volume:
- 2013
- Issue:
- 2013
- Issue Sort Value:
- 2013-2013-2013-0000
- Page Start:
- Page End:
- Publication Date:
- 2013-12-12
- Subjects:
- Computer vision -- Periodicals
Computer vision
Periodicals
Electronic journals
006.37 - Journal URLs:
- https://www.hindawi.com/journals/isrn/contents/isrn.machine.vision/ ↗
- DOI:
- 10.1155/2013/261956 ↗
- Languages:
- English
- ISSNs:
- 2090-7796
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 17533.xml