VIAME: Video and Image Analytics in Marine Environments
Abstract
Seafood sustainability is predicated on healthy fish and shellfish populations. Recent developments in the collection of large-volume optical survey data by autonomous underwater vehicles (AUVs), stationary camera arrays, and... [ view full abstract ]
Seafood sustainability is predicated on healthy fish and shellfish populations. Recent developments in the collection of large-volume optical survey data by autonomous underwater vehicles (AUVs), stationary camera arrays, and towed vehicles has made it possible for fishery scientists to generate species-specific, size-structured abundance estimates for different species of marine organisms via imagery. The immense volume of data collected by such survey methods quickly exceeds manual processing capacity and creates a strong need for automatic image analysis. To address these challenges, we have created the Video and Image Analytics for Marine Environments (VIAME) toolkit, at viametoolkit.org. VIAME is an open-source computer vision software platform designed to integrate common image and video analytics, such as stereo calibration, object detection and object classification, into a sequential data processing pipeline that is easy to program, multi-threaded, and generic. The system provides a cross-language common interface for each of these components, multiple implementations of each, as well as unified methods for evaluating and visualizing the results of different methods for accomplishing the same task. Most recently, the ability to measure fish, to run detector ensembles, and to rapidly train models for novel detection tasks has been integrated into the platform. Sponsored by the Automated Imagery Analysis Strategic Initiative of the United States National Oceanic and Atmospheric Administration’s (NOAA) National Marine Fisheries Service (NMFS), VIAME will be deployed at multiple NOAA Fisheries Science Centers to continue improving scientific data that support stock assessments. VIAME will also be freely available to the global community of marine researchers.
Authors
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Matthew Dawkins
(Kitware Inc.)
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Jon Crall
(Kitware Inc.)
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David Zhang
(SRI)
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Linus Sherrill
(Kitware Inc.)
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Lakshman Prasad
(Los Alamos National Laboratory)
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Kresimir Williams
(NOAA Fisheries)
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Michael Piacentino
(SRI)
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Anthony Hoogs
(Kitware Inc.)
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Benjamin Richards
(NOAA Fisheries)
Topic Areas
Topics: Fisheries, aquaculture, and the oceans , Topics: Conservation engineering , Topics: Ocean science technology
Session
S-168 » Optical Technology and Computer Vision for Marine Conservation and Sustainable Management (16:00 - Monday, 25th June, Tubau 2)