Road Traffic Monitoring from UAV Images Using Deep Learning Networks
In this paper, we propose a deep neural network-based method for estimating speed of vehicles on roads automatically from videos recorded using unmanned aerial vehicle (UAV). The proposed method includes the following; (1) detecting and tracking vehicles by analyzing the videos, (2) calculating the...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/20/4027 |
| _version_ | 1827678673020387328 |
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| author | Sungwoo Byun In-Kyoung Shin Jucheol Moon Jiyoung Kang Sang-Il Choi |
| author_facet | Sungwoo Byun In-Kyoung Shin Jucheol Moon Jiyoung Kang Sang-Il Choi |
| author_sort | Sungwoo Byun |
| collection | DOAJ |
| description | In this paper, we propose a deep neural network-based method for estimating speed of vehicles on roads automatically from videos recorded using unmanned aerial vehicle (UAV). The proposed method includes the following; (1) detecting and tracking vehicles by analyzing the videos, (2) calculating the image scales using the distances between lanes on the roads, and (3) estimating the speeds of vehicles on the roads. Our method can automatically measure the speed of the vehicles from the only videos recorded using UAV without additional information in both directions on the roads simultaneously. In our experiments, we evaluate the performance of the proposed method with the visual data at four different locations. The proposed method shows 97.6% recall rate and 94.7% precision rate in detecting vehicles, and it shows error (root mean squared error) of 5.27 km/h in estimating the speeds of vehicles. |
| first_indexed | 2024-03-10T06:14:20Z |
| format | Article |
| id | doaj.art-6f6c9caad6c84a5d80e9936a961b01f0 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T06:14:20Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-6f6c9caad6c84a5d80e9936a961b01f02023-11-22T19:53:00ZengMDPI AGRemote Sensing2072-42922021-10-011320402710.3390/rs13204027Road Traffic Monitoring from UAV Images Using Deep Learning NetworksSungwoo Byun0In-Kyoung Shin1Jucheol Moon2Jiyoung Kang3Sang-Il Choi4Department of Computer Science and Engineering, Dankook University, Yongin-si 16890, Gyeonggi-do, KoreaWearable Thinking Center, Dankook University, Yongin-si 16890, Gyeonggi-do, KoreaDepartment of Computer Engineering and Computer Science, California State University Long Beach, Long Beach, CA 90840, USACollege of Software Convergence, Dankook University, Yongin-si 16890, Gyeonggi-do, KoreaDepartment of Computer Science and Engineering, Dankook University, Yongin-si 16890, Gyeonggi-do, KoreaIn this paper, we propose a deep neural network-based method for estimating speed of vehicles on roads automatically from videos recorded using unmanned aerial vehicle (UAV). The proposed method includes the following; (1) detecting and tracking vehicles by analyzing the videos, (2) calculating the image scales using the distances between lanes on the roads, and (3) estimating the speeds of vehicles on the roads. Our method can automatically measure the speed of the vehicles from the only videos recorded using UAV without additional information in both directions on the roads simultaneously. In our experiments, we evaluate the performance of the proposed method with the visual data at four different locations. The proposed method shows 97.6% recall rate and 94.7% precision rate in detecting vehicles, and it shows error (root mean squared error) of 5.27 km/h in estimating the speeds of vehicles.https://www.mdpi.com/2072-4292/13/20/4027deep learningUAV imagetraffic monitoringobject detectionobject trackingimage segmentation |
| spellingShingle | Sungwoo Byun In-Kyoung Shin Jucheol Moon Jiyoung Kang Sang-Il Choi Road Traffic Monitoring from UAV Images Using Deep Learning Networks Remote Sensing deep learning UAV image traffic monitoring object detection object tracking image segmentation |
| title | Road Traffic Monitoring from UAV Images Using Deep Learning Networks |
| title_full | Road Traffic Monitoring from UAV Images Using Deep Learning Networks |
| title_fullStr | Road Traffic Monitoring from UAV Images Using Deep Learning Networks |
| title_full_unstemmed | Road Traffic Monitoring from UAV Images Using Deep Learning Networks |
| title_short | Road Traffic Monitoring from UAV Images Using Deep Learning Networks |
| title_sort | road traffic monitoring from uav images using deep learning networks |
| topic | deep learning UAV image traffic monitoring object detection object tracking image segmentation |
| url | https://www.mdpi.com/2072-4292/13/20/4027 |
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