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AOS-Simulation

Airborne Optical Sectioning Simulation based on:

We show that automated person detection under occlusion conditions can be significantly improved by combining multi-perspective images before classification. Here, we employed image integration by Airborne Optical Sectioning (AOS) - a synthetic aperture imaging technique that uses camera drones to capture unstructured thermal light fields - to achieve this with a precision/recall of 96/93%. Finding lost or injured people in dense forests is not generally feasible with thermal recordings, but becomes practical with use of AOS integral images. Our findings lay the foundation for effective future search and rescue technologies that can be applied in combination with autonomous or manned aircraft. They can also be beneficial for other fields that currently suffer from inaccurate classification of partially occluded people, animals, or objects.

Publications github

Additional publications and software modules for AOS based search and rescue can be found on the author's main repository.

Simulation html

The simulation is based on three.js and runs on all major platforms and web browsers.

Navigation (zoom, pan, rotate) is available via mouse and touch events. User controls allow the adjustment of several parameters for:

  • drone
    • camera
    • cpu
  • forest
    • trees
      • branching
      • trunk
    • persons
      • activities
  • material
    • color

The simulation data may be exported as a zip file for further processing and analysis.

Online browser status

An online version of this repository code can be found here.

Application electron platform

Additional a standalone application is available for automated and parallelized data export.

app

More details can be found in INSTALL.md.

Source download

Drone from clara.io:

Persons from mixamo.com:

Textures from texture.ninja:

Fonts from fonts.google.com:

License license

MIT

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