Variational surface interpolation from sparse point and normal data
(2007) In IEEE Transactions on Pattern Analysis and Machine Intelligence 29(1). p.181-184- Abstract
- Many visual cues for surface reconstruction from known views are sparse in nature, e.g., specularities, surface silhouettes, and salient features in an otherwise textureless region. Often, these cues are the only information available to an observer. To allow these constraints to be used either in conjunction with dense constraints such as pixel-wise similarity, or alone, we formulate such constraints in a variational framework. We propose a sparse variational constraint in the level set framework, enforcing a surface to pass through a specific point, and a sparse variational constraint on the surface normal along the observed viewing direction, as is the nature of, e.g., specularities. These constraints are capable of reconstructing... (More)
- Many visual cues for surface reconstruction from known views are sparse in nature, e.g., specularities, surface silhouettes, and salient features in an otherwise textureless region. Often, these cues are the only information available to an observer. To allow these constraints to be used either in conjunction with dense constraints such as pixel-wise similarity, or alone, we formulate such constraints in a variational framework. We propose a sparse variational constraint in the level set framework, enforcing a surface to pass through a specific point, and a sparse variational constraint on the surface normal along the observed viewing direction, as is the nature of, e.g., specularities. These constraints are capable of reconstructing surfaces from extremely sparse data. The approach has been applied and validated on the shape from specularities problem. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/685814
- author
- Solem, Jan Erik
LU
; Aanaes, Henrik
and Heyden, Anders
LU
- organization
- publishing date
- 2007
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- surface interpolation, multiple view stereo, specularities, shape from, level set method, variational methods, computer vision
- in
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- volume
- 29
- issue
- 1
- pages
- 181 - 184
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- wos:000241988300016
- scopus:33947219268
- ISSN
- 1939-3539
- DOI
- 10.1109/TPAMI.2007.250610
- language
- English
- LU publication?
- yes
- id
- dc307291-0955-42bd-be44-9cd77c3297cd (old id 685814)
- date added to LUP
- 2016-04-01 16:40:31
- date last changed
- 2023-09-18 22:55:51
@article{dc307291-0955-42bd-be44-9cd77c3297cd, abstract = {{Many visual cues for surface reconstruction from known views are sparse in nature, e.g., specularities, surface silhouettes, and salient features in an otherwise textureless region. Often, these cues are the only information available to an observer. To allow these constraints to be used either in conjunction with dense constraints such as pixel-wise similarity, or alone, we formulate such constraints in a variational framework. We propose a sparse variational constraint in the level set framework, enforcing a surface to pass through a specific point, and a sparse variational constraint on the surface normal along the observed viewing direction, as is the nature of, e.g., specularities. These constraints are capable of reconstructing surfaces from extremely sparse data. The approach has been applied and validated on the shape from specularities problem.}}, author = {{Solem, Jan Erik and Aanaes, Henrik and Heyden, Anders}}, issn = {{1939-3539}}, keywords = {{surface interpolation; multiple view stereo; specularities; shape from; level set method; variational methods; computer vision}}, language = {{eng}}, number = {{1}}, pages = {{181--184}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Transactions on Pattern Analysis and Machine Intelligence}}, title = {{Variational surface interpolation from sparse point and normal data}}, url = {{http://dx.doi.org/10.1109/TPAMI.2007.250610}}, doi = {{10.1109/TPAMI.2007.250610}}, volume = {{29}}, year = {{2007}}, }