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Authors: Qian Li ; Yi Kong and Shi-ming Xia

Affiliation: PLA University of Science and Technology, China

Keyword(s): Outdoor Image, Weather Recognition, Power Spectrum Slop, SVM, Decision Tree.

Abstract: To improve the quality of video surveillance in outdoor and automatic acquire of the weather situations, a method to recognize weather phenomenon based on outdoor images is presented. There are three features of our method: firstly, the features, such as the power spectrum slope, contrast, noise and saturation and so on are extracted, after analysing the effect of weather situations on image; secondly, a decision tree is constructed in accordance with the distance between the features; thirdly, when every SVM classifier on the non-leaf node of the decision tree is constructed, some features are selected by assigning the weight. The experiment results prove that the proposed method can effectively recognize the weather situations in outdoor.

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Paper citation in several formats:
Li, Q.; Kong, Y. and Xia, S. (2014). A Method of Weather Recognition based on Outdoor Images. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP; ISBN 978-989-758-004-8; ISSN 2184-4321, SciTePress, pages 510-516. DOI: 10.5220/0004724005100516

@conference{visapp14,
author={Qian Li. and Yi Kong. and Shi{-}ming Xia.},
title={A Method of Weather Recognition based on Outdoor Images},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP},
year={2014},
pages={510-516},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004724005100516},
isbn={978-989-758-004-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP
TI - A Method of Weather Recognition based on Outdoor Images
SN - 978-989-758-004-8
IS - 2184-4321
AU - Li, Q.
AU - Kong, Y.
AU - Xia, S.
PY - 2014
SP - 510
EP - 516
DO - 10.5220/0004724005100516
PB - SciTePress