(Created page with " == Abstract == Structure from Motion or the sparse 3D reconstruction out of individual photos is a long studied topic in computer vision. Yet none of the existing reconstruc...")
 
m (Scipediacontent moved page Draft Content 489541222 to Gool et al 2018a)
 
(No difference)

Latest revision as of 11:26, 25 January 2021

Abstract

Structure from Motion or the sparse 3D reconstruction out of individual photos is a long studied topic in computer vision. Yet none of the existing reconstruction pipelines fully addresses a progressive scenario where images are only getting available during the reconstruction process and intermediate results are delivered to the user. Incremental pipelines are capable of growing a 3D model but often get stuck in local minima due to wrong (binding) decisions taken based on incomplete information. Global pipelines on the other hand need the access to the complete viewgraph and are not capable of delivering intermediate results. In this paper we propose a new reconstruction pipeline working in a progressive manner rather than in a batch processing scheme. The pipeline is able to recover from failed reconstructions in early stages, avoids to take binding decisions, delivers a progressive output and yet maintains the capabilities of existing pipelines. We demonstrate and evaluate our method on diverse challenging public and dedicated datasets including those with highly symmetric structures and compare to the state of the art.


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.1007/978-3-030-01225-0_2 under the license http://www.springer.com/tdm
https://dblp.uni-trier.de/db/journals/corr/corr1803.html#abs-1803-07349,
https://link.springer.com/chapter/10.1007/978-3-030-01225-0_2,
https://ui.adsabs.harvard.edu/abs/2018arXiv180307349L/abstract,
http://openaccess.thecvf.com/content_ECCV_2018/html/Alex_Locher_Progressive_Structure_from_ECCV_2018_paper.html,
http://www.arxiv-vanity.com/papers/1803.07349,
https://eccv2018.org/openaccess/content_ECCV_2018/html/Alex_Locher_Progressive_Structure_from_ECCV_2018_paper.html,
https://rd.springer.com/chapter/10.1007/978-3-030-01225-0_2,
https://academic.microsoft.com/#/detail/2963217126
Back to Top

Document information

Published on 01/01/2018

Volume 2018, 2018
DOI: 10.1007/978-3-030-01225-0_2
Licence: Other

Document Score

0

Views 2
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?