TY - RPRT
TI - Automated Identification of Fish and Other Aquatic Life in Underwater Video
AU - Blowers, S
AU - Evans, J
AU - McNally, K
AB - Marine Scotland tasked MarynSol to provide an overview of the current state of computer vision technologies for automated detection of aquatic life in underwater video, the objective being to provide a development route for a tool to analyse the large amount of historic video footage without the need for human supervision. This task was split into two parts: the first being a review of the literature of the current technologies and the second being a case study incorporating some of the more promising candidates for this problem space.There is considerable immediate potential to make use of such methods for the automated detection and identification of fish and other fauna in underwater video material collected in camera boxes attached to open ended trawl nets; during monitoring at tidal turbines and at wind turbine bases; and at video based fish counters and in the video validation of fish counters using other technology. It is hoped that such methods may well allow effective progress to be made with archived video material which various parties hold which is waiting for review.
DA - 2020/08//
PY - 2020
SP - 62
PB - MarynSol Ltd
SN - Scottish Marine and Freshwater Science Vol 11 No 18
UR - https://data.marine.gov.scot/dataset/automated-identification-fish-and-other-aquatic-life-underwater-video
LA - English
KW - Marine Energy
KW - Wind Energy
KW - Fixed Offshore Wind
KW - Fish
KW - Invertebrates
ER -