ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture
Underwater object tracking holds considerable significance in the field of ocean engineering. Additionally, it serves as a crucial component in the operations of autonomous underwater vehicles (AUVs), particularly during tasks associated with capturing marine organisms. However, the attenuation and...
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MDPI AG
2024-11-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/12/11/2092 |
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| author | Ju He Yang Yu Hongyu Wei Hu Xu |
| author_facet | Ju He Yang Yu Hongyu Wei Hu Xu |
| author_sort | Ju He |
| collection | DOAJ |
| description | Underwater object tracking holds considerable significance in the field of ocean engineering. Additionally, it serves as a crucial component in the operations of autonomous underwater vehicles (AUVs), particularly during tasks associated with capturing marine organisms. However, the attenuation and scattering of light result in shortcomings such as poor contrast in underwater images. Additionally, the motion deformation of marine organisms poses a significant challenge. Therefore, existing tracking algorithms face difficulty in direct application to underwater object tracking. To overcome this challenge, we propose a novel tracking architecture for the marine organism capturing of AUVs called ULOTrack. ULOTrack is based on a performance discrimination and re-detection framework and constitutes three modules: (1) an object tracker, which can extract multi-feature information of the underwater target; (2) a multi-layer tracking performance discriminator, which serves the purpose of evaluating the stability of the current tracking state, thereby reducing potential model drift; and (3) lightweight detection, which can predict the candidate boxes to relocate the lost tracked underwater object. We conduct comprehensive experiments to validate the efficacy of the designed modules. Finally, the results of the experimentation demonstrate that ULOTrack significantly outperforms existing approaches. In the future, we aim to carefully scrutinize and select more suitable features to enhance tracking accuracy and speed. |
| format | Article |
| id | doaj-art-992cbb3e8dc04a5d9fb3a87ecc0ef328 |
| institution | OA Journals |
| issn | 2077-1312 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-992cbb3e8dc04a5d9fb3a87ecc0ef3282025-08-20T02:05:03ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-11-011211209210.3390/jmse12112092ULOTrack: Underwater Long-Term Object Tracker for Marine Organism CaptureJu He0Yang Yu1Hongyu Wei2Hu Xu3School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaUnderwater object tracking holds considerable significance in the field of ocean engineering. Additionally, it serves as a crucial component in the operations of autonomous underwater vehicles (AUVs), particularly during tasks associated with capturing marine organisms. However, the attenuation and scattering of light result in shortcomings such as poor contrast in underwater images. Additionally, the motion deformation of marine organisms poses a significant challenge. Therefore, existing tracking algorithms face difficulty in direct application to underwater object tracking. To overcome this challenge, we propose a novel tracking architecture for the marine organism capturing of AUVs called ULOTrack. ULOTrack is based on a performance discrimination and re-detection framework and constitutes three modules: (1) an object tracker, which can extract multi-feature information of the underwater target; (2) a multi-layer tracking performance discriminator, which serves the purpose of evaluating the stability of the current tracking state, thereby reducing potential model drift; and (3) lightweight detection, which can predict the candidate boxes to relocate the lost tracked underwater object. We conduct comprehensive experiments to validate the efficacy of the designed modules. Finally, the results of the experimentation demonstrate that ULOTrack significantly outperforms existing approaches. In the future, we aim to carefully scrutinize and select more suitable features to enhance tracking accuracy and speed.https://www.mdpi.com/2077-1312/12/11/2092visual perceptionunderwater observationunderwater object trackingautonomous underwater vehicletracking discriminator |
| spellingShingle | Ju He Yang Yu Hongyu Wei Hu Xu ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture Journal of Marine Science and Engineering visual perception underwater observation underwater object tracking autonomous underwater vehicle tracking discriminator |
| title | ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture |
| title_full | ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture |
| title_fullStr | ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture |
| title_full_unstemmed | ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture |
| title_short | ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture |
| title_sort | ulotrack underwater long term object tracker for marine organism capture |
| topic | visual perception underwater observation underwater object tracking autonomous underwater vehicle tracking discriminator |
| url | https://www.mdpi.com/2077-1312/12/11/2092 |
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