An Open-Source Platform for Underwater Image and Video Analytics

Abstract

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.

Cite

Text

Dawkins et al. "An Open-Source Platform for Underwater Image and Video Analytics." IEEE/CVF Winter Conference on Applications of Computer Vision, 2017. doi:10.1109/WACV.2017.105

Markdown

[Dawkins et al. "An Open-Source Platform for Underwater Image and Video Analytics." IEEE/CVF Winter Conference on Applications of Computer Vision, 2017.](https://mlanthology.org/wacv/2017/dawkins2017wacv-open/) doi:10.1109/WACV.2017.105

BibTeX

@inproceedings{dawkins2017wacv-open,
  title     = {{An Open-Source Platform for Underwater Image and Video Analytics}},
  author    = {Dawkins, Matthew and Sherrill, Linus and Fieldhouse, Keith and Hoogs, Anthony and Richards, Benjamin L. and Zhang, David and Prasad, Lakshman and Williams, Kresimir and Lauffenburger, Nathan and Wang, Gaoang},
  booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision},
  year      = {2017},
  pages     = {898-906},
  doi       = {10.1109/WACV.2017.105},
  url       = {https://mlanthology.org/wacv/2017/dawkins2017wacv-open/}
}