Individual Surveillance Around Parked Aircraft at Nighttime: Thermal Infrared Vision-Based Human Action Recognition
IEEE Transactions on Systems, Man, and Cybernetics: Systems
; 53(2):1084-1094, 2023.
Article
in English
| Scopus | ID: covidwho-2240290
ABSTRACT
The COVID-19 crisis has led to an unusually large number of commercial aircraft being currently parked or stored. For airlines, airports, and civil aviation authorities around the world, monitoring, and protecting these parked aircraft to prevent them from causing human-made damage are becoming urgent problems that are receiving increasing attention. In this study, we use thermal infrared monitoring videos to establish a framework for individual surveillance around parked aircraft by proposing a human action recognition (HAR) algorithm. As the focus of this article, the proposed HAR algorithm seamlessly integrates a preprocessing module in which a novel data structure is constructed to introduce spatiotemporal information of the action;a convolutional neural network-based module for spatial feature extraction;a triple-layer convolutional long short-term memory network for temporal feature extraction;and two fully connected layers for classification. Moreover, because no infrared dataset is available for the HAR task on airport grounds at nighttime, we present a dataset called IIAR-30, which consists of eight action categories that frequently occur on airport grounds and 2000 video clips. The experimental results on the IIAR-30 dataset demonstrated that the recognition accuracy of the proposed method was higher than 96%. We also further evaluated the effectiveness of the proposed method by comparing it with five baselines and four other methods. © 2022 IEEE.
Airport security; Airports; Brain; Classification (of information); Convolution; Extraction; Infrared radiation; Long short-term memory; Monitoring; Multilayer neural networks; Security systems; Training aircraft; Convolutional long short-term memory; Convolutional neural network; Features extraction; Human action recognition; Human-action recognition; Individual surveillance; Spatiotemporal phenomenon; Surveillance; Task analysis; Thermal infrared videos; Video; Feature extraction; Convolutional long short-term memory (ConvLSTM); convolutional neural network (CNN); human action recognition (HAR); thermal infrared (TIR) video
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Year:
2023
Document Type:
Article
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