A Low-Level Active Vision Framework for Collaborative Unmanned Aircraft Systems Martin

  • Martin Danelljan(B), Fahad Shahbaz Khan, Michael Felsberg K
  • Om
  • Fredrik Heintz, Piotr Rudol, Mariusz Wzorek J
 et al. 
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Abstract

Abstract. Micro unmanned aerial vehicles are becoming increasingly interesting for aiding and collaborating with human agents in myriads of applications, but in particular they are useful for monitoring inaccessible or dangerous areas. In order to interact with and monitor humans, these systems need robust and real-time computer vision subsystems that allow to detect and follow persons. In this work, we propose a low-level active vision framework to accom- plish these challenging tasks. Based on the LinkQuad platform, we present a system study that implements the detection and tracking of people under fully autonomous flight conditions, keeping the vehicle within a certain distance of a person. The framework integrates state-of-the-art methods from visual detection and tracking, Bayesian filtering, and AI- based control. The results from our experiments clearly suggest that the proposed framework performs real-time detection and tracking of persons in complex scenarios. Keywords:

Author-supplied keywords

  • Visual tracking · Visual surveillance · Micro UAV

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Authors

  • Karl Granstr¨ Martin Danelljan(B), Fahad Shahbaz Khan, Michael Felsberg

  • Om

  • Jonas kvarnström Fredrik Heintz, Piotr Rudol, Mariusz Wzorek

  • Om

  • and Patrick Doherty

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