by Greybits
Squidle+ is a platform designed for exploration, management and annotation of georeferenced images & video data. It allows for multiple annotation schemes and provides functionality to translate between them, which facilitates collaboration, makes it possible to import historical data and provides access to large data sets for training machine learning algorithms, which ultimately have the potential to provide a scalable, cost-effective solution for dealing with huge volumes of underwater imagery and video. It can be set up to run in the cloud, securely on a local network within an organisation, or even onboard a ship for realtime capture and analysis or data. Squidle+ has been recommended as the platform of choice for Australia’s National Environmental Science Program SOP manuals for benthic AUV and towed platform image management, annotation and analysis.
  • ClientSeveral
  • Date22 July 2015
  • CatagoriesData Management, API, open source
See for yourself

Flexible annotation schemes

  • There is no one size fits all when it comes to annotation schemes. Many have tried and failed to create an annotation scheme that suites the needs of all potential users, and now we have a variety of competing standardised schemes that exist.
  • SQUIDLE+ approaches this by providing a flexible annotation system which allows users to annotate data using their annotation scheme of choice (whether selected from existing standard schemes or a new custom one).
  • Instead of enforcing a single scheme, it provides the capability to translate between different annotation schemes, which means that data labeled under one scheme can be viewed under another making sure that all annotated data is maintained in a consistent format.
  • In addition, it will allow multiple labels per point as well as apply additional tags and free-form comments per annotation.

Collaborative / automated labeling

  • Much of our scientific understanding of benthic environments ultimately depends on human interpretation of seafloor imagery.
  • Traditional approaches, largely reliant on manual annotation of a small subsets by human experts, will not scale to the increasing demand for quantitative understanding of marine habitats for science and regulatory compliance, nor to the increasing volume of seafloor images.
  • This platform seeks to enable and manage collaborative human-machine labelling invoking human experts, citizen scientists and machine learning algorithms to achieve validated accuracy and predictable time frames.

Education & outreach

  • With the advances in high bandwidth communications and social media, education & outreach activities have become commonplace on ocean-bound research cruises.
  • It is possible to leverage the development effort in creating science tools to facilitate outreach goals, opening up the potential to acquire large volumes of crowd-sourced data that can compliment science objectives and engage the general public.
  • We have already had some successes in this area.

Flexible data storage

  • Requiring that all data is available/uploaded to the centralised web server poses a barrier for adding new data from other sources, duplicating data that is often already available elsewhere online.
  • Many national marine observing programs, are mandated to put data online in an openly accessible location.
  • These distributed data storage facilities should be leveraged to reduce data duplication and inconsistencies, and will also mean that data can be made readily available much more quickly. Using the a framework for interpreting flexible meta data formats, it takes minutes (instead of days) to import datasets and get them ready for detailed annotation.

"Media object" annotation

  • The new system will enable the same consistent labels to be applied to different media objects (images, video and large-scale mosaics).
  • It will also offer the capability for defining validation sets based on other annotation sets for assessing annotation quality.
  • There is a widespread global need for a flexible web-based video annotation tool.
  • Using pre-existing video hosting technology, this is a relatively straightforward extension to the current platform.

In-field data annotation

  • Unannotated data from the field can be considered to be a liability in the sense that it often results in huge repositories of images and video that need to be assessed at a later time.
  • Real-time annotation for video and stills using the same annotation interface running a local caching database that can be easily synchronised with the online system post cruise, would make it possible to better leverage time and resources in the field and help to reduce the “post processing debt”.