Detection of Wildfires along Transmission Lines Using Deep Time and Space Features


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Resumo

Traditional wildfire detection methods are of low efficiency and cannot meet user needs, a novel method based on deep time and space features along transmission line is proposed in this paper, which uses ViBe algorithm to detect movements in videos, and extracts static deep feature in the space domain and dynamic optical flow feature in the time domain respectively. At last the deep convolutional neural network model in cascade is used to classify and find out real wildfire regions. By using combined deep features extracted from dynamic time-domain and static space-domain respectively, our method can eliminate the interference of movements of other objects with similar colors.

Sobre autores

Jie Yuan

Jiangsu Electric Power Information Technology Co., Ltd.

Autor responsável pela correspondência
Email: java_mc@163.com
República Popular da China, Nanjing, 210000

Lidong Wang

Qianjiang College

Email: java_mc@163.com
República Popular da China, Hangzhou, Zhejiang, 310036

Peng Wu

Jiangsu Electric Power Information Technology Co., Ltd.

Email: java_mc@163.com
República Popular da China, Nanjing, 210000

Chao Gao

State Grid Jiangsu Electric Power Company

Email: java_mc@163.com
República Popular da China, Nanjing, 210024

Lingqing Sun

Jiangsu Electric Power Information Technology Co., Ltd.

Email: java_mc@163.com
República Popular da China, Nanjing, 210000

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