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People Detection and Tracking Using an On-Board Drone Camera

  • Cristian Cifuentes-GarcíaEmail author
  • Daniel González-Medina
  • Ismael García-Varea
Conference paper
  • 337 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1093)

Abstract

The problem of people detection and tracking in unmanned ground vehicles has been studied in depth in computer vision and autonomous robotics research communities. Different well-known proposals have already been proposed to solve the problem of people detection and tracking using machine vision algorithms. However, for unmanned aerial vehicles, it is still a subject of research today. The lack of high-quality sensors and on-board cameras and the capability to process the data collected in real-time makes it difficult to achieve optimal solutions in real-time. In this work, we propose to use machine vision algorithms to process in real-time the images collected by the camera of a drone and subsequently performing the detection and tracking of people who are located in the environment. The proposal was experimentally evaluated comparing different semantic segmentation techniques. Finally, to validate the proposal, a real scenario was created and carried out, which consisted of detecting and tracking people with a drone autonomously in a controlled environment.

Keywords

People detection and tracking Semantic segmentation Computer vision Robotics Drone 

Notes

Acknowledgments

This work has been partially sponsored by the Regional Council of Education, Culture and Sports of Castilla-La Mancha under grant number SBPLY/17/180501/000493, supported with Feder funds.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Cristian Cifuentes-García
    • 1
    Email author
  • Daniel González-Medina
    • 1
  • Ismael García-Varea
    • 1
  1. 1.University of Castilla-La ManchaAlbaceteSpain

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