Sung-Jun Lee, Myung-Il Roh, Min-Jae Oh, Youngsoo Seok, Won-Jae Lee, June-Beom Lee, Hyun Soo Kim, "Image-based Object Detection and Tracking Method for Ship Navigation," Proceedings of ICCAS(International Conference on Computer Applications in Shipbuilding) 2019, Rotterdam, Netherlands, pp. 89-92, 2019.09.24-26
Sung-Jun Lee, Myung-Il Roh, Min-Jae Oh, Youngsoo Seok, Won-Jae Lee, June-Beom Lee, Hyun Soo Kim, "Image-based Object Detection and Tracking Method for Ship Navigation," Proceedings of ICCAS 2019, Rotterdam, Netherlands, pp. 89-92, 2019.09.24-26
첨부 '1' |
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Abstract | Situational awareness is one of the most essential abilities of unmanned vessels. Even in the case of manned vessels, situational awareness can contribute to safe navigation by detecting and alerting potential collisions. Although radar and AIS(Automatic Identification System) are widely used for detection, it is necessary to use vision cameras that can take place of human eyes to detect near objects and identify object types. In this study, we performed machine vision based object detection and tracking for the situational awareness in maritime environment. For object detection, the state-of-the-art detection algorithms and their various backbone CNN(Convolutional Neural Network) models were applied; a two-stage detection model derived from Faster R-CNN and a single-stage detection model based on YOLO were implemented and tested in this study. The performance in mAP(mean average precision) score of each detection model was evaluated and compared. For object tracking, we surveyed not only conventional correlation filtering algorithms but also deep learning algorithms using LSTM(Long Short-Term Memory) network models. All the trainable detection and tracking models were trained by maritime domain image dataset. Performance of each model was estimated under maritime visionary environment. |
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Publication Date | 2019-09-24 |
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Jeong-Ho Park, Myung-Il Roh, Hye-Won Lee, Jisang Ha, Yeong-Min Jo, Nam-Sun Son, "Detection and Tracking Methods of Maritime Obstacles Using Multiple Cameras", Proceedings of ICDM 2022, Siheung, Korea, 2022.04.28-29
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Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, Seung-Ho Ham, "A Block Lifting Method with Wire Ropes Based on Deep Reinforcement Learning", Proceedings of ICDM 2022, Si-Heung, Korea, 2022.04.28-29
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Dong-Guen Jeong, Myung-Il Roh, Ki-Su Kim, Jun-Sik Lee, Dae-Hyuk Kim, Wang-Seok Jang, "A Method for Route Planning of Small Ships in Coastal Areas", Proceedings of ICDM 2022, Si-Heung, Korea, 2022.04.28-29
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Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, "Deep Reinforcement Learning-Based Ship Collision Avoidance Considering Collision Risk", Proceedings of TEAM 2022, Istanbul, Turkey, pp. 268, 2021.12.06-07
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Ki-Su Kim, Myung-Il Roh, "Optimization of the Arrangement Design of a Ship Considering the Multiple Performance", Proceedings of ACSMO 2020, Seoul, Korea, pp. 167, 2020.11.23-25
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Jisang Ha, Myung-Il Roh, Hye-Won Lee, Jong-Ho Eun, Jong-Jin Park, Hyun-Joe Kim, "A Method of the Collision Avoidance of a Ship Using Real-time AIS Data", Proceedings of ACSMO 2020, Seoul, Korea, pp. 106, 2020.11.23-25
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Hye-Won Lee, Myung-Il Roh, Seung-Ho Ham, "Method for the Accurate and Automatic Operation of Offshore Floating Cranes for the Block Erection in Shipyards", Proceedings of OMAE 2020, Held in Virtual Conference, 2020.08.03-07
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Jisang Ha, Myung-Il Roh, Jong-Hyeok Lee, Jin-Hyeok Kim, Min-Chul Kong, Seung-Ho Ham, "Integrated Ship Remote Operating System Based on Digital Twin Technology", Proceedings of TEAM 2019, Tainan, Taiwan, pp. 106, 2019.10.14-17
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Luman Zhao, Myung-Il Roh, Hye-Won Lee, Do-Hyun Chun, Sung-Jun Lee, "A Collision Avoidance Method of Multi-ships Based on Deep Reinforcement Learning Considering COLREGs," Proceedings of ICCAS 2019, Rotterdam, Netherlands, pp. 85-88, 2019.09.24-26
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Sung-Jun Lee, Myung-Il Roh, Min-Jae Oh, Youngsoo Seok, Won-Jae Lee, June-Beom Lee, Hyun Soo Kim, "Image-based Object Detection and Tracking Method for Ship Navigation," Proceedings of ICCAS 2019, Rotterdam, Netherlands, pp. 89-92, 2019.09.24-26