Vision-based object detection and tracking for autonomous navigation of underwater robots
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, D. | - |
dc.contributor.author | Kim, G. | - |
dc.contributor.author | Kim, D. | - |
dc.contributor.author | Myung, H. | - |
dc.contributor.author | Choi, H.-T. | - |
dc.date.accessioned | 2021-08-03T05:42:54Z | - |
dc.date.available | 2021-08-03T05:42:54Z | - |
dc.date.issued | 2012 | - |
dc.identifier.issn | 0029-8018 | - |
dc.identifier.uri | https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/1043 | - |
dc.description.abstract | Underwater robots have been an emerging research area being at the intersection of the field of robotics and oceanic engineering. Their applications include environmental monitoring, oceanographic mapping, and infrastructure inspections in deep sea. In performing these tasks, the ability of autonomous navigation is the key to a success, especially with the limited communications in underwater environments. Considering the highly dynamic and three-dimensional environments, the autonomous navigation technologies including path planning and tracking have been one of the interesting but challenging tasks in the field of study. Cameras have not been at the center of attention as an underwater sensor due to the limited detection ranges and the poor visibility. Use of visual data from cameras, however, is still an attractive method for underwater sensing and it is especially effective in the close range detections. In this paper, the vision-based object detection and tracking techniques for underwater robots have been studied in depth. In order to overcome the limitations of cameras and to make use of the full advantages of image data, a number of approaches have been tested. The topics include color restoration algorithm for the degraded underwater images, detection and tracking methods for underwater target objects. The feasibilities of the proposed algorithms have been demonstrated in the experiments with an underwater robot platform and the results have been analyzed both qualitatively and quantitatively. ? 2012 Elsevier Ltd. All rights reserved. | - |
dc.format.extent | 10 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.title | Vision-based object detection and tracking for autonomous navigation of underwater robots | - |
dc.type | Article | - |
dc.publisher.location | 영국 | - |
dc.identifier.doi | 10.1016/j.oceaneng.2012.04.006 | - |
dc.identifier.scopusid | 2-s2.0-84861161534 | - |
dc.identifier.bibliographicCitation | Ocean Engineering, v.48, pp 59 - 68 | - |
dc.citation.title | Ocean Engineering | - |
dc.citation.volume | 48 | - |
dc.citation.startPage | 59 | - |
dc.citation.endPage | 68 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | sci | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Autonomous navigation | - |
dc.subject.keywordPlus | Close range | - |
dc.subject.keywordPlus | Color restoration | - |
dc.subject.keywordPlus | Deep sea | - |
dc.subject.keywordPlus | Detection and tracking | - |
dc.subject.keywordPlus | Detection range | - |
dc.subject.keywordPlus | Environmental Monitoring | - |
dc.subject.keywordPlus | Image data | - |
dc.subject.keywordPlus | Limited communication | - |
dc.subject.keywordPlus | Object Detection | - |
dc.subject.keywordPlus | Object Tracking | - |
dc.subject.keywordPlus | Oceanic engineering | - |
dc.subject.keywordPlus | Poor visibility | - |
dc.subject.keywordPlus | Three-dimensional environment | - |
dc.subject.keywordPlus | Underwater environments | - |
dc.subject.keywordPlus | Underwater image | - |
dc.subject.keywordPlus | Underwater robots | - |
dc.subject.keywordPlus | Underwater sensors | - |
dc.subject.keywordPlus | Underwater target | - |
dc.subject.keywordPlus | Underwater vision | - |
dc.subject.keywordPlus | Vision based | - |
dc.subject.keywordPlus | Visual data | - |
dc.subject.keywordPlus | Algorithms | - |
dc.subject.keywordPlus | Cameras | - |
dc.subject.keywordPlus | Computer vision | - |
dc.subject.keywordPlus | Image reconstruction | - |
dc.subject.keywordPlus | Motion planning | - |
dc.subject.keywordPlus | Navigation | - |
dc.subject.keywordPlus | Navigation systems | - |
dc.subject.keywordPlus | Object recognition | - |
dc.subject.keywordPlus | Robots | - |
dc.subject.keywordPlus | Tracking (position) | - |
dc.subject.keywordPlus | Autonomous underwater vehicles | - |
dc.subject.keywordPlus | algorithm | - |
dc.subject.keywordPlus | autonomous underwater vehicle | - |
dc.subject.keywordPlus | detection method | - |
dc.subject.keywordPlus | environmental monitoring | - |
dc.subject.keywordPlus | image processing | - |
dc.subject.keywordPlus | mapping | - |
dc.subject.keywordPlus | marine technology | - |
dc.subject.keywordPlus | robotics | - |
dc.subject.keywordPlus | sensor | - |
dc.subject.keywordPlus | tracking | - |
dc.subject.keywordPlus | vision | - |
dc.subject.keywordAuthor | Object detection | - |
dc.subject.keywordAuthor | Object tracking | - |
dc.subject.keywordAuthor | Underwater image restoration | - |
dc.subject.keywordAuthor | Underwater robot | - |
dc.subject.keywordAuthor | Underwater vision | - |
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