2026-09-19T22:55:34Zhttps://ecommons.cornell.edu/server/oai/requestoai:ecommons.cornell.edu:1813/1031342026-05-15T19:40:02Zcom_1813_35col_1813_47
Gao, Xinyu
Ferrari, Silvia
Hariharan, Bharath
2021-03-12T17:43:53Z
2021-03-12T17:43:53Z
2020-08
ProQuest Submission ID: 11038
ProQuest Publication ID: 28089028
https://hdl.handle.net/1813/103134
https://doi.org/10.7298/51wz-9d62
13277836
56 pages
Maritime surveillance system installed on-board is crucial in protecting commercial vessels worldwide, which suffer potential losses due to the maritime piracy assault. On-board camera provides a way of monitoring suspicious activities at a low cost. However, the maritime environment poses challenges in detecting mobile targets because the water background is highly dynamic. This thesis addresses the problem of detecting and tracking mobile targets in the maritime environment utilizing an on-board camera. An approach based on optical flow is used to detect mobile targets presented in the camera scene. The camera measurement model and target kinematics model are proposed such that targets can be tracked utilizing the Bayesian filtering technique. A sensor planning strategy based on expected entropy reduction (EER) is developed to select optimal sensor field of view (FoV) locations such that the expected entropy reduction is maximized.
en
An Expected Entropy Reduction (EER) Approach to Target Tracking in Maritime Environment for On-board Camera
dissertation or thesis
https://catalog.library.cornell.edu/catalog/13277836
application/pdf
Mechanical Engineering
Cornell University
Master of Science
M.S., Mechanical Engineering
https://hdl.handle.net/1813/59810
Publication
Cornell Theses and Dissertations
Gao, Xinyu
5893a6ea-7af3-41d7-abc6-04bcd26ab5df
open.access
open.access
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<Abstract>Maritime surveillance system installed on-board is crucial in protecting commercial vessels worldwide, which suffer potential losses due to the maritime piracy assault. On-board camera provides a way of monitoring suspicious activities at a low cost. However, the maritime environment poses challenges in detecting mobile targets because the water background is highly dynamic. This thesis addresses the problem of detecting and tracking mobile targets in the maritime environment utilizing an on-board camera. An approach based on optical flow is used to detect mobile targets presented in the camera scene. The camera measurement model and target kinematics model are proposed such that targets can be tracked utilizing the Bayesian filtering technique. A sensor planning strategy based on expected entropy reduction (EER) is developed to select optimal sensor field of view (FoV) locations such that the expected entropy reduction is maximized.</Abstract>
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