Multiple-view geometry under the Linfinity-norm
This paper presents a new framework for solving geometric structure and motion problems based on Linfinity-norm. Instead of using the common sum-of-squares cost-function, that is, the L2-norm, the model-fitting errors are measured using the L-norm. Unlike traditional methods based on L2, our framewo...
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1998. - 30(2008), 9 vom: 15. Sept., Seite 1603-17 |
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| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2008
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence |
| Sujets: | Journal Article |
| Résumé: | This paper presents a new framework for solving geometric structure and motion problems based on Linfinity-norm. Instead of using the common sum-of-squares cost-function, that is, the L2-norm, the model-fitting errors are measured using the L-norm. Unlike traditional methods based on L2, our framework allows for efficient computation of global estimates. We show that a variety of structure and motion problems, for example, triangulation, camera resectioning and homography estimation can be recast as quasi-convex optimization problems within this framework. These problems can be efficiently solved using Second-Order Cone Programming (SOCP) which is a standard technique in convex optimization. The methods have been implemented in Matlab and the resulting toolbox has been made publicly available. The algorithms have been validated on real data in different settings on problems with small and large dimensions and with excellent performance |
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| Description: | Date Completed 23.09.2008 Date Revised 11.07.2008 published: Print Citation Status MEDLINE |
| ISSN: | 0162-8828 |
| DOI: | 10.1109/TPAMI.2007.70824 |