Workshop at the European Conference on Computer Vision

ECCV 2014: Computer Vision - ECCV 2014 Workshops pp 223-237 | Cite as

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

  • Martin Danelljan
  • Fahad Shahbaz Khan
  • Michael Felsberg
  • Karl Granström
  • Fredrik Heintz
  • Piotr Rudol
  • Mariusz Wzorek
  • Jonas Kvarnström
  • Patrick Doherty
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8925)

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 accomplish 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

Visual tracking Visual surveillance Micro UAV Active vision 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Martin Danelljan
    • 1
  • Fahad Shahbaz Khan
    • 1
  • Michael Felsberg
    • 1
  • Karl Granström
    • 1
  • Fredrik Heintz
    • 1
  • Piotr Rudol
    • 1
  • Mariusz Wzorek
    • 1
  • Jonas Kvarnström
    • 1
  • Patrick Doherty
    • 1
  1. 1.Linköping UniversityLinköpingSweden

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