Two-Class Weather Classification

Given a single outdoor image, this paper proposes a collaborative learning approach for labeling it as either sunny or cloudy. Never adequately addressed, this twoclass classification problem is by no means trivial given the great variety of outdoor images. Our weather feature combines special cues...

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Bibliographic Details
Published in2014 IEEE Conference on Computer Vision and Pattern Recognition pp. 3718 - 3725
Main Authors Lu, Cewu, Lin, Di, Jia, Jiaya, Tang, Chi-Keung
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.06.2014
Subjects
Classification
Climatology
Clouds
Computer vision
Construction
Feature
Histograms
Image color analysis
Labeling
Learning
Meteorology
Outdoor
Pattern recognition
Scene
Training
Vectors
Weather
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Summary:Given a single outdoor image, this paper proposes a collaborative learning approach for labeling it as either sunny or cloudy. Never adequately addressed, this twoclass classification problem is by no means trivial given the great variety of outdoor images. Our weather feature combines special cues after properly encoding them into feature vectors. They then work collaboratively in synergy under a unified optimization framework that is aware of the presence (or absence) of a given weather cue during learning and classification. Extensive experiments and comparisons are performed to verify our method. We build a new weather image dataset consisting of 10K sunny and cloudy images, which is available online together with the executable.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Conference-1
ObjectType-Feature-3
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SourceType-Conference Papers & Proceedings-2
ISSN:1063-6919
1063-6919
2575-7075
DOI:10.1109/CVPR.2014.475