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http://hdl.handle.net/1942/22872
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DC Field | Value | Language |
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dc.contributor.author | PUT, Jeroen | - |
dc.contributor.author | MICHIELS, Nick | - |
dc.contributor.author | BEKAERT, Philippe | - |
dc.date.accessioned | 2016-12-07T09:11:19Z | - |
dc.date.available | 2016-12-07T09:11:19Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Wilson, Richard C.; Hancock, Edwin R.; Smith, William A. P. (Ed.). Proceedings of the British Machine Vision Conference 2016, BMVA Press,p. 25.1-25.10 | - |
dc.identifier.isbn | 1901725596 | - |
dc.identifier.uri | http://hdl.handle.net/1942/22872 | - |
dc.description.abstract | Recent advances in machine learning have enabled the recognition of high-level categories of materials with a reasonable accuracy. With these techniques, we can construct a per-pixel material labeling from a single image. We observe that groups of high-level material categories have distinct chromaticity distributions. This fact can be used to predict the range of the absolute chromaticity values of objects, provided the material is correctly labeled. We explore whether these constraints are useful in the context of the intrinsic images problem. This paper describes how to leverage material category identification to boost estimation results in state-of-the-art intrinsic images datasets. | - |
dc.description.sponsorship | This work was partly made possible by the Agency for Innovation by Science and Technology in Flanders (IWT). | - |
dc.language.iso | en | - |
dc.publisher | BMVA Press | - |
dc.rights | (c) 2016. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms. | - |
dc.subject.other | intrinsic images; priors; chromaticity; materials; relighting | - |
dc.title | Material-Specific Chromaticity Priors | - |
dc.type | Proceedings Paper | - |
local.bibliographicCitation.authors | Wilson, Richard C. | - |
local.bibliographicCitation.authors | Hancock, Edwin R. | - |
local.bibliographicCitation.authors | Smith, William A. P. | - |
local.bibliographicCitation.conferencedate | 19-22/09/2016 | - |
local.bibliographicCitation.conferencename | The British Machine Vision Conference (BMVC 2016) | - |
local.bibliographicCitation.conferenceplace | York, UK | - |
dc.identifier.epage | 25.10 | - |
dc.identifier.spage | 25.1 | - |
local.bibliographicCitation.jcat | C1 | - |
local.publisher.place | Durham | - |
local.type.refereed | Refereed | - |
local.type.specified | Proceedings Paper | - |
dc.identifier.url | www.bmva.org/bmvc/2016/toc.html | - |
local.bibliographicCitation.btitle | Proceedings of the British Machine Vision Conference 2016 | - |
item.fullcitation | PUT, Jeroen; MICHIELS, Nick & BEKAERT, Philippe (2016) Material-Specific Chromaticity Priors. In: Wilson, Richard C.; Hancock, Edwin R.; Smith, William A. P. (Ed.). Proceedings of the British Machine Vision Conference 2016, BMVA Press,p. 25.1-25.10. | - |
item.fulltext | With Fulltext | - |
item.contributor | PUT, Jeroen | - |
item.contributor | MICHIELS, Nick | - |
item.contributor | BEKAERT, Philippe | - |
item.accessRights | Open Access | - |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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paper025.pdf | Published version | 2.22 MB | Adobe PDF | View/Open |
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