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)


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)
Number of pages7
ISBN (Print)9781479944958
Publication statusPublished - 15 Jan 2015


  • autonomous object detection
  • mobile visual surveillance platform
  • UAV

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