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SVM and RGB-D Sensor Based Gesture Recognition for UAV Control

  • Wilbert G. Aguilar
  • Bryan Cobeña
  • Guillermo Rodriguez
  • Vinicio S. Salcedo
  • Brayan Collaguazo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10851)

Abstract

This research has the purpose of allowing anyone, with or without experience handling micro aerial vehicles, to operate unmanned aerial vehicles (UAV) in a natural and intuitive way, unlike typical interfaces that need experience and knowledge in piloting to be used. To achieve this, our approach uses gesture recognition, based on machine learning with Support Vector Machine (SVM) for classification and a RGB-D sensor for the feature extraction. Tests for recognition with different Kernel-SVM and for the RGB-D sensor with different levels of light were carried out.

Keywords

Machine learning Support Vector Machine Gesture recognition RGB-D sensor UAV 

Notes

Acknowledgement

This work is part of the project “Perception and localization system for autonomous navigation of rotor micro aerial vehicle in gps-denied environments, VisualNavDrone”, 2016-PIC-024, from the Universidad de las Fuerzas Armadas ESPE, directed by Dr. Wilbert G. Aguilar.

Conflicts of Interest

The authors declare no conflict of interest.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Wilbert G. Aguilar
    • 1
    • 2
  • Bryan Cobeña
    • 1
  • Guillermo Rodriguez
    • 1
  • Vinicio S. Salcedo
    • 1
  • Brayan Collaguazo
    • 1
  1. 1.CICTE Research CenterUniversidad de las Fuerzas Armadas ESPESangolquíEcuador
  2. 2.GREC Research GroupUniversitat Politècnica de CatalunyaBarcelonaSpain

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