Weather recognition via classification labels and weather-cue maps
Wang, Zhigang2; Lu, Xiaoqiang1; Li, Xuelong2; Hua, Lulu2; Zhao, Bin2
SourcePattern Recognition
2019-11
Volume95Pages:272-284
ISSN00313203
DOI10.1016/j.patcog.2019.06.017
Rank2
English Abstract

Although it is of great importance to recognize weather conditions automatically, this task has not been explored thoroughly in practice. Generally, most approaches in the literature simply treat it as a common image classification task, i.e., assigning a certain weather label to each image. However, there are significant differences between weather recognition and common image classification, since several weather conditions tend to occur simultaneously, like foggy and cloudy. Obviously, a single weather label is insufficient to provide a comprehensive description of the weather conditions. In this case, we propose to utilize auxiliary weather-cues, e.g., black clouds and blue sky, for comprehensive weather description. Specifically, a multi-task framework is designed to jointly deal with the weather-cue segmentation task and weather classification task. Benefit from the intrinsic relationships lying in the two tasks, exploring the information of weather-cues can not only provide a comprehensive description of weather conditions, but also help the weather classification task to learn more effective features, and further improve the performance. Besides, we construct two large-scale weather recognition datasets equipped with both weather labels and segmentation masks of weather-cues. Experiment results demonstrate the excellent performance of our approach. The constructed two datasets will be available at https://github.com/wzgwzg/Multitask_Weather. © 2019 Elsevier Ltd

Language英语
PublisherElsevier Ltd
Citation statistics
Content Type期刊论文
URIhttp://www.corc.org.cn/handle/1471x/2469374
Collection西安光学精密机械研究所_光学影像学习与分析中心
Corresponding AuthorLu, Xiaoqiang
Affiliation1.The Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an; Shaanxi; 710119, China
2.School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an; Shaanxi; 710072, China;
Recommended Citation
GB/T 7714
Wang, Zhigang,Lu, Xiaoqiang,Li, Xuelong,et al. Weather recognition via classification labels and weather-cue maps[J]. Pattern Recognition,2019,95:272-284.
APA Wang, Zhigang,Lu, Xiaoqiang,Li, Xuelong,Hua, Lulu,&Zhao, Bin.(2019).Weather recognition via classification labels and weather-cue maps.Pattern Recognition,95,272-284.
MLA Wang, Zhigang,et al."Weather recognition via classification labels and weather-cue maps".Pattern Recognition 95(2019):272-284.
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