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Cherry Zhang

dblp:21/9990 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2013
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 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
2 papers
Image and video processing · 50% Computational photography and imaging · 50%

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

TopicWeightPapersLastEvidence papers
Computational photography and imaging › color science
color appearance modeling		 0.322013
Image-Based Separation of Reflective and Fluorescent Components Using Illumination Variant and Invariant Color · IEEE Trans. Pattern Anal. Mach. Intell. 2013
Separating reflective and fluorescent components of an image · CVPR 2011
Image and video processing
image decomposition		 0.322013
Image-Based Separation of Reflective and Fluorescent Components Using Illumination Variant and Invariant Color · IEEE Trans. Pattern Anal. Mach. Intell. 2013
Separating reflective and fluorescent components of an image · CVPR 2011

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

linear model · 0.3independent component analysis · 0.3
YearPublicationVenuePosition
2013 Image-Based Separation of Reflective and Fluorescent Components Using Illumination Variant and Invariant Color
abstract
Traditionally, researchers tend to exclude fluorescence from color appearance algorithms in computer vision and image processing because of its complexity. In reality, fluorescence is a very common phenomenon observed in many objects, from gems and corals, to different kinds of writing paper, and to our clothes. In this paper, we provide detailed theories of fluorescence phenomenon. In particular, we show that the color appearance of fluorescence is unaffected by illumination in which it differs from ordinary reflectance. Moreover, we show that the color appearance of objects with reflective and fluorescent components can be represented as a linear combination of the two components. A linear model allows us to separate the two components using images taken under unknown illuminants using independent component analysis (ICA). The effectiveness of the proposed method is demonstrated using digital images of various fluorescent objects.
Cherry Zhang, Imari Sato
 IEEE Trans. Pattern Anal. Mach. Intell.1
2011 Separating reflective and fluorescent components of an image
abstract
Traditionally researchers tend to exclude fluorescence from color appearance algorithms in computer vision and image processing because of its complexity. In reality, fluorescence is a very common phenomenon observed in many objects, from gems and corals, to different kinds of writing paper, and to our clothes. In this paper, we provide detailed theories of fluorescence phenomenon. In particular, we show that the color appearance of fluorescence is unaffected by illumination in which it differs from ordinary reflectance. Moreover, we show that the color appearance of objects with reflective and fluorescent components can be represented as a linear combination of the two components. A linear model allows us to separate the two components using images taken under two unknown illuminants using independent component analysis(ICA). The effectiveness of the proposed method is demonstrated using digital images of various fluorescent objects.
Cherry Zhang, Imari Sato
 CVPR1