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Conference Paper The Analysis of Image Acquisition Method for Anti-UAV Surveillance using Cameras Image
Cited 12 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Young-il Kim, Yeo Geon Min, Park Seong Hee, Jeong Wun-Cheol, Song Soonyong, Heo Tae-Wook
Issue Date
2020-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2020, pp.549-554
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC49870.2020.9289164
Abstract
As the number of cases where human life and property are threatened by illegal use of UAV is rapidly increasing, a technology for detecting illegal UAV using deep learning algorithm is being researched. In order for the deep learning algorithm to work, an appropriate UAV object image size and quality are required. Unfortunately, in detecting a small UAV using a camera sensor, when the object image of the camera becomes small, the detection distance of the UAV is reduced due to the difficulty of detecting the UAV. Therefore, a large number of cameras are required to expand the detection distance. This paper suggests the methodology for configuring UAV surveillance area for image acquisition in terms of reducing the required number of cameras. Four methods for constructing the UAV surveillance area considering the optical limitations of the camera are proposed, and compared the proposed methods using a simple thin lens camera model.
KSP Keywords
Acquisition method, Camera model, Camera sensor, Detection distance, Object image, Small UAVs, Thin lens, UAV surveillance, deep learning(DL), deep learning algorithm, image acquisition