TY - GEN
T1 - Precise Localization of a UAV with Single Vision Camera and Deep Learning
AU - Kim, Hyeong Tae
AU - Kim, Hwangnam
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No.2020R1A2C1012389).
Publisher Copyright:
© 2020 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - This paper suggests a novel method of detecting and estimating the position of Unmanned Aerial Vehicle (UAV) with a single monocular camera only. As the leverage of UAV is keep on increasing, the related research has been extremely developed. To successfully use a UAV in a variety of missions, a precise localization technique is essential. However, there is still a lack of research to accurately measure the vehicle's present altitude. Thus, this study conducted a simple but accurate altitude measurement method using a camera. First, UAV detection is initially proceeded by using a deep learning approach. After determining that the object displayed in the image is UAV, the altitude is calculated with a distance measuring formula using the camera's Field of View (FOV). Besides, zooming, cropping, and some image processing are performed to enhance the accuracy of the altitude value. As a result, average errors of less than 5% and errors of up to 60cm were obtained, which is an improvement over previous altitude measurement techniques. This method can calibrate the altitude of the UAV immediately in a relatively inexpensive and simple way.
AB - This paper suggests a novel method of detecting and estimating the position of Unmanned Aerial Vehicle (UAV) with a single monocular camera only. As the leverage of UAV is keep on increasing, the related research has been extremely developed. To successfully use a UAV in a variety of missions, a precise localization technique is essential. However, there is still a lack of research to accurately measure the vehicle's present altitude. Thus, this study conducted a simple but accurate altitude measurement method using a camera. First, UAV detection is initially proceeded by using a deep learning approach. After determining that the object displayed in the image is UAV, the altitude is calculated with a distance measuring formula using the camera's Field of View (FOV). Besides, zooming, cropping, and some image processing are performed to enhance the accuracy of the altitude value. As a result, average errors of less than 5% and errors of up to 60cm were obtained, which is an improvement over previous altitude measurement techniques. This method can calibrate the altitude of the UAV immediately in a relatively inexpensive and simple way.
KW - Altitude
KW - Deep learning
KW - FOV
KW - Localization
KW - UAV
UR - http://www.scopus.com/inward/record.url?scp=85100410394&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM42002.2020.9322358
DO - 10.1109/GLOBECOM42002.2020.9322358
M3 - Conference contribution
AN - SCOPUS:85100410394
T3 - 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings
BT - 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Global Communications Conference, GLOBECOM 2020
Y2 - 7 December 2020 through 11 December 2020
ER -