An Open-Source Platform for Underwater Image and Video Analytics
| Autor: | David C. Zhang, Kresimir Williams, Anthony Hoogs, N. Lauffenburger, Gaoang Wang, Linus Sherrill, Matthew Dawkins, Benjamin L. Richards, Keith Fieldhouse, Lakshman Prasad |
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| Rok vydání: | 2017 |
| Předmět: |
0106 biological sciences
Contextual image classification Computer science business.industry 010604 marine biology & hydrobiology Interface (computing) 02 engineering and technology Object (computer science) 01 natural sciences Pipeline (software) Object detection Software Analytics 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Implementation |
| Zdroj: | WACV |
| DOI: | 10.1109/wacv.2017.105 |
| Popis: | Global fisheries and the future of sustainable seafood are predicated on healthy populations of various species of fish and shellfish. Recent developments in the collection of large-volume optical 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 devices quickly exceeds manual processing capacity and creates a strong need for automatic image analysis. This paper presents 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. |
| Databáze: | OpenAIRE |
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