Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
4-1-2021 12:00 AM
End Date
9-1-2021 12:00 AM
Description
Video surveillance can be used to monitor recreational and commercial vessels on inland waters. It is difficult to identify vessels on the basis of registration numbers alone, especially when structure and size are not standardized in a way that allows for easy recognition. In this paper, we propose a novel vessel identification method that can work continuously on streams with a high compression rate or visible compression artifacts. This method can identify all types of moving vessels during daylight. It should work with existing video monitoring systems used to monitor inland waters. When a vessel has hull inscriptions, the method can identify that vessel. If hull inscriptions are not present, the method identifies the direction of movement of the vessel. The tests were performed by real-time video playback of prerecorded samples in the test environment. The method correctly identifies 94% of vessels and the performance indicates that it is suitable for practical application.
Identification of Vessels on Inland Waters Using Low-Quality Video Streams
Online
Video surveillance can be used to monitor recreational and commercial vessels on inland waters. It is difficult to identify vessels on the basis of registration numbers alone, especially when structure and size are not standardized in a way that allows for easy recognition. In this paper, we propose a novel vessel identification method that can work continuously on streams with a high compression rate or visible compression artifacts. This method can identify all types of moving vessels during daylight. It should work with existing video monitoring systems used to monitor inland waters. When a vessel has hull inscriptions, the method can identify that vessel. If hull inscriptions are not present, the method identifies the direction of movement of the vessel. The tests were performed by real-time video playback of prerecorded samples in the test environment. The method correctly identifies 94% of vessels and the performance indicates that it is suitable for practical application.
https://aisel.aisnet.org/hicss-54/st/video_analytics/2