Optimal estimation of perspective camera pose
(2006) 18th International Conference on Pattern Recognition, ICPR 2006 2. p.5-8- Abstract
- In this paper we propose apractical and efficient method for finding the globally optimal solution to the problem of camera pose estimation for calibrated cameras. While traditional methods may get trapped in local minima, due to the non-convexity of the problem, we have developed an approach that guarantees global optimality. The scheme is based on ideas from global optimization theory, in particular, convex under-estimators in combination with branch and bound. We provide aprovably optimal algorithm and demonstrate good performance on both synthetic and real data.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/617183
- author
- Olsson, Carl LU ; Kahl, Fredrik LU and Oskarsson, Magnus LU
- organization
- publishing date
- 2006
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Calibrated cameras, Global optimization theory, Camera pose estimation
- host publication
- Proceedings - International Conference on Pattern Recognition
- volume
- 2
- pages
- 5 - 8
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 18th International Conference on Pattern Recognition, ICPR 2006
- conference location
- Hong Kong, China
- conference dates
- 2006-08-20 - 2006-08-24
- external identifiers
-
- wos:000240678300002
- scopus:34047218043
- ISSN
- 1051-4651
- DOI
- 10.1109/ICPR.2006.909
- language
- English
- LU publication?
- yes
- id
- 9597a773-c9b2-49f7-923a-323b92eb302b (old id 617183)
- date added to LUP
- 2016-04-01 16:48:45
- date last changed
- 2022-04-23 00:44:15
@inproceedings{9597a773-c9b2-49f7-923a-323b92eb302b, abstract = {{In this paper we propose apractical and efficient method for finding the globally optimal solution to the problem of camera pose estimation for calibrated cameras. While traditional methods may get trapped in local minima, due to the non-convexity of the problem, we have developed an approach that guarantees global optimality. The scheme is based on ideas from global optimization theory, in particular, convex under-estimators in combination with branch and bound. We provide aprovably optimal algorithm and demonstrate good performance on both synthetic and real data.}}, author = {{Olsson, Carl and Kahl, Fredrik and Oskarsson, Magnus}}, booktitle = {{Proceedings - International Conference on Pattern Recognition}}, issn = {{1051-4651}}, keywords = {{Calibrated cameras; Global optimization theory; Camera pose estimation}}, language = {{eng}}, pages = {{5--8}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Optimal estimation of perspective camera pose}}, url = {{http://dx.doi.org/10.1109/ICPR.2006.909}}, doi = {{10.1109/ICPR.2006.909}}, volume = {{2}}, year = {{2006}}, }