Vision-based detection and tracking of marine vehicles using convolutional neural networks = 합성곱 신경망을 이용한 영상기반 선박 탐지 및 경로 추정

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Marine vehicle tracking is gaining relevance nowadays in the research community. This has to do with the fact that current development in technology has propitiated a tendency towards autonomous navigation, with all the potential advantages this implies. A solution to this problem will be the focus of this dissertation. Based on previous work in the field, a tracking system using computer vision with a monocular camera arrangement is proposed. In this system, some possibilities of improvement have been identified and implemented. They can be grouped in two blocks: those related to perception and those related to the model of tracking. In the former, modern techniques based on deep-learning have been applied, whereas in the latter, mathematical models have been developed aiming to improve and complement the existing system. The results of the proposed methods show improvements in the robustness and accuracy of the tracking of marine vehicles in the tested scenarios.
Advisors
Kim, Jin Whanresearcher김진환researcher
Description
한국과학기술원 :기계공학과,
Publisher
한국과학기술원
Issue Date
2017
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 기계공학과, 2017.8,[iv, 40 p. :]

Keywords

Marine vehicles tracking▼acomputer vision▼aconvolutional neural network; 해양 선박 추적▼a영상처리▼a합성곱신경망

URI
http://hdl.handle.net/10203/242895
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=718534&flag=dissertation
Appears in Collection
ME-Theses_Master(석사논문)
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