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Optical Flow-Guided Deep Convolutional Neural Networks for UAV Detection in Infrared Videos

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成果类型:
会议论文
作者:
Yang, Xin;Wang, Yi-zheng;Wang, Gang
通讯作者:
Wang, G
作者机构:
[Yang, Xin] Univ South China, Hengyang, Peoples R China.
[Yang, Xin; Wang, Gang; Wang, Yi-zheng] Beijing Inst Basic Med Sci, Beijing, Peoples R China.
[Wang, Gang] Chinese Inst Brain Res, Beijing, Peoples R China.
通讯机构:
[Wang, G ] B
Beijing Inst Basic Med Sci, Beijing, Peoples R China.
Chinese Inst Brain Res, Beijing, Peoples R China.
语种:
英文
关键词:
optical flow;video object detection;feature fusion;post-processing;convolutional neural network
期刊:
2022 IEEE 7TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION ENGINEERING, ICITE
年:
2022
页码:
457-461
会议名称:
IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE)
会议时间:
NOV 11-13, 2022
会议地点:
Beijing, PEOPLES R CHINA
会议主办单位:
[Yang, Xin] Univ South China, Hengyang, Peoples R China.^[Yang, Xin;Wang, Yi-zheng;Wang, Gang] Beijing Inst Basic Med Sci, Beijing, Peoples R China.^[Wang, Gang] Chinese Inst Brain Res, Beijing, Peoples R China.
出版地:
345 E 47TH ST, NEW YORK, NY 10017 USA
出版者:
IEEE
ISBN:
978-1-6654-6007-1
基金类别:
Beijing Natural Science Foundation [4214060]; National Natural Science Foundation of China [62102443]
机构署名:
本校为第一机构
摘要:
Early warning of small civilian UAVs is a critical issue in the field of public security and is a challenging task in object detection. Video object detection methods based on deep convolution neural networks have attracted increasing attention over recent years. The object detection algorithm designed for static images can hardly be used directly in video object detection, due to motion blur, out-of-focus, etc. Traditional methods mainly apply temporal information to address this problem. In this paper, we proposed a method based on optical flow for UAV video object detection, employing optic...

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