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Vision-Based Moving Obstacle Detection and Tracking in Paddy Field Using Improved Yolov3 and Deep SORT
https://kitami-it.repo.nii.ac.jp/records/2000438
https://kitami-it.repo.nii.ac.jp/records/2000438e678bf59-d49b-4958-9e31-defeb5eabb9c
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
sensors-20-04082.pdf (4 MB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||||||||||||||||||
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| 公開日 | 2023-07-20 | |||||||||||||||||||||
| タイトル | ||||||||||||||||||||||
| タイトル | Vision-Based Moving Obstacle Detection and Tracking in Paddy Field Using Improved Yolov3 and Deep SORT | |||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||
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| 言語 | eng | |||||||||||||||||||||
| 資源タイプ | ||||||||||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||||||||
| アクセス権 | ||||||||||||||||||||||
| アクセス権 | open access | |||||||||||||||||||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||||||||||||||||||
| 著者 |
Zhengjun Qiu
× Zhengjun Qiu
× Nan Zhao
× Lei Zhou
× Mengcen Wang
× Liangliang Yang
× Hui Fang
× Yong He
× Yufei Liu
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| 抄録 | ||||||||||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||||||||||
| 内容記述 | Using intelligent agricultural machines in paddy fields has received great attention. An obstacle avoidance system is required with the development of agricultural machines. In order to make the machines more intelligent, detecting and tracking obstacles, especially the moving obstacles in paddy fields, is the basis of obstacle avoidance. To achieve this goal, a red, green and blue (RGB) camera and a computer were used to build a machine vision system, mounted on a transplanter. A method that combined the improved You Only Look Once version 3 (Yolov3) and deep Simple Online and Realtime Tracking (deep SORT) was used to detect and track typical moving obstacles, and figure out the center point positions of the obstacles in paddy fields. The improved Yolov3 has 23 residual blocks and upsamples only once, and has new loss calculation functions. Results showed that the improved Yolov3 obtained mean intersection over union (mIoU) score of 0.779 and was 27.3% faster in processing speed than standard Yolov3 on a self-created test dataset of moving obstacles (human and water buffalo) in paddy fields. An acceptable performance for detecting and tracking could be obtained in a real paddy field test with an average processing speed of 5–7 frames per second (FPS), which satisfies actual work demands. In future research, the proposed system could support the intelligent agriculture machines more flexible in autonomous navigation. |
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| 言語 | en | |||||||||||||||||||||
| 書誌情報 |
en : Sensors 巻 20, 号 15, p. 4082-4082, 発行日 2020-07 |
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| DOI | ||||||||||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||||||||
| 関連識別子 | https://doi.org/10.3390/s20154082 | |||||||||||||||||||||
| 権利 | ||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||
| 権利情報 | c2020 by the authors. Licensee MDPI | |||||||||||||||||||||
| 出版者 | ||||||||||||||||||||||
| 出版者 | MDPI | |||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||
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| 言語 | en | |||||||||||||||||||||
| 値 | publisher | |||||||||||||||||||||
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| 出版タイプ | VoR | |||||||||||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||||||||||
