A real-time approach for autonomous detection and tracking of moving objects from UAV

Pouria Sadeghi Tehran, Christopher Clarke, Plamen Parvanov Angelov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

A new approach to autonomously detect and track moving objects in a video captured by a moving camera from a UAV in real-time is proposed in this paper. The introduced approach replaces the need for a human operator to perform video analytics by autonomously detecting moving objects and clustering them for tracking purposes. The effectiveness of the introduced approach is tested on the footage taken from a real UAV and the evaluation results are demonstrated in this paper.
Original languageEnglish
Title of host publication2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS)
PublisherIEEE
Pages43-49
Number of pages7
ISBN (Print)9781479944958
DOIs
Publication statusPublished - 15 Jan 2015

Keywords

  • autonomous object detection
  • mobile visual surveillance platform
  • UAV

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