A Computer Vision Encyclopedia-Based Framework with Illustrative UAV Applications

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This paper presents the structure of an encyclopedia-based framework (EbF) in which to develop computer vision systems that incorporate the principles of agile development with focussed knowledge-enhancing information. The novelty of the EbF is that it specifies both the use of drop-in modules, to enable the speedy implementation and modification of systems by the operator, and it incorporates knowledge of the input image-capture devices and presentation preferences. This means that the system includes automated parameter selection and operator advice and guidance. Central to this knowledge-enhanced framework is an encyclopedia that is used to store all information pertaining to the current system operation and can be used by all of the imaging modules and computational runtime components. This ensures that they can adapt to changes within the system or its environment. We demonstrate the implementation of this system over three use cases in computer vision for unmanned aerial vehicles (UAV) showing how it is easy to control and set up by novice operators utilising simple computational wrapper scripts.

Original languageEnglish
Article number29
Pages (from-to)1-11
Number of pages11
Issue number3
Publication statusPublished - 4 Mar 2021


  • Deblocking
  • Drone
  • Encyclopedia
  • Framework
  • SfM
  • Super-resolution


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