Baptiste Mazin

dblp:119/1505 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-authorArtificial intelligence and machine learning · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Computational photography and imaging · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational photography and imaging
color constancy
0.212015
Estimation of Illuminants From Projections on the Planckian Locus · IEEE Trans. Image Process. 2015
Computational photography and imaging › color constancy
illuminant estimation
0.212015
Estimation of Illuminants From Projections on the Planckian Locus · IEEE Trans. Image Process. 2015

Methods — techniques the papers use, named apart from their topics

voting procedure · 0.2chromaticity space projection · 0.2
YearPublicationVenuePosition
2015 Estimation of Illuminants From Projections on the Planckian Locus
abstract
This paper introduces a new approach for the automatic estimation of illuminants in a digital color image. The method relies on two assumptions. First, the image is supposed to contain at least a small set of achromatic pixels. The second assumption is physical and concerns the set of possible illuminants, assumed to be well approximated by black body radiators. The proposed scheme is based on a projection of selected pixels on the Planckian locus in a well chosen chromaticity space, followed by a voting procedure yielding the estimation of the illuminant. This approach is very simple and learning-free. The voting procedure can be extended for the detection of multiple illuminants when necessary. Experiments on various databases show that the performances of this approach are similar to those of the best learning-based state-of-the-art algorithms.
Baptiste Mazin, Julie Delon, Yann Gousseau
IEEE Trans. Image Process.1
2012 Combining color and geometry for local image matching
Baptiste Mazin, Julie Delon, Yann Gousseau
ICPR1