Adaptive Color Constancy Using Faces.
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| Title: | Adaptive Color Constancy Using Faces. |
|---|---|
| Authors: | Bianco, Simone1, Schettini, Raimondo1 |
| Source: | IEEE Transactions on Pattern Analysis & Machine Intelligence. Aug2014, Vol. 36 Issue 8, p1505-1518. 14p. |
| Subjects: | Object constancy (Psychoanalysis), Face perception, Human facial recognition software, Image recognition (Computer vision), Lighting, Mathematical models |
| Abstract: | In this work we design an adaptive color constancy algorithm that, exploiting the skin regions found in faces, is able to estimate and correct the scene illumination. The algorithm automatically switches from global to spatially varying color correction on the basis of the illuminant estimations on the different faces detected in the image. An extensive comparison with both global and local color constancy algorithms is carried out to validate the effectiveness of the proposed algorithm in terms of both statistical and perceptual significance on a large heterogeneous data set of RAW images containing faces. [ABSTRACT FROM PUBLISHER] |
| Copyright of IEEE Transactions on Pattern Analysis & Machine Intelligence is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 97011207 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Adaptive Color Constancy Using Faces. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Bianco%2C+Simone%22">Bianco, Simone</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Schettini%2C+Raimondo%22">Schettini, Raimondo</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Pattern+Analysis+%26+Machine+Intelligence%22">IEEE Transactions on Pattern Analysis & Machine Intelligence</searchLink>. Aug2014, Vol. 36 Issue 8, p1505-1518. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Object+constancy+%28Psychoanalysis%29%22">Object constancy (Psychoanalysis)</searchLink><br /><searchLink fieldCode="DE" term="%22Face+perception%22">Face perception</searchLink><br /><searchLink fieldCode="DE" term="%22Human+facial+recognition+software%22">Human facial recognition software</searchLink><br /><searchLink fieldCode="DE" term="%22Image+recognition+%28Computer+vision%29%22">Image recognition (Computer vision)</searchLink><br /><searchLink fieldCode="DE" term="%22Lighting%22">Lighting</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In this work we design an adaptive color constancy algorithm that, exploiting the skin regions found in faces, is able to estimate and correct the scene illumination. The algorithm automatically switches from global to spatially varying color correction on the basis of the illuminant estimations on the different faces detected in the image. An extensive comparison with both global and local color constancy algorithms is carried out to validate the effectiveness of the proposed algorithm in terms of both statistical and perceptual significance on a large heterogeneous data set of RAW images containing faces. [ABSTRACT FROM PUBLISHER] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IEEE Transactions on Pattern Analysis & Machine Intelligence is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=97011207 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1109/TPAMI.2013.2297710 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1505 Subjects: – SubjectFull: Object constancy (Psychoanalysis) Type: general – SubjectFull: Face perception Type: general – SubjectFull: Human facial recognition software Type: general – SubjectFull: Image recognition (Computer vision) Type: general – SubjectFull: Lighting Type: general – SubjectFull: Mathematical models Type: general Titles: – TitleFull: Adaptive Color Constancy Using Faces. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Bianco, Simone – PersonEntity: Name: NameFull: Schettini, Raimondo IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2014 Type: published Y: 2014 Identifiers: – Type: issn-print Value: 01628828 Numbering: – Type: volume Value: 36 – Type: issue Value: 8 Titles: – TitleFull: IEEE Transactions on Pattern Analysis & Machine Intelligence Type: main |
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