Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
A Real-time Supervised Learning Approach for Sky Segmentation Onboard Unmanned Aerial Vehicles
Year:2016
Research Areas
  • Aerial robots,
  • Recognition of patterns,
  • Computer vision
Information
Abstract
Vision-based sky segmentation and horizon line detection can be extremely useful to perform important tasks onboard Unmanned Aerial Vehicles (UAVs), such as pose estimation and collision avoidance. Most of the existing vision-based solutions use traditional image processing methods to identify the horizon line. This results in good overall accuracy and fast computation times. However, difficult environmental conditions such as a foggy or cloudy skies hinder correct sky segmentation. This paper proposes a solution for sky segmentation in RGB images using a supervised Machine Learning approach by first splitting the image into fixed-size patches, extracting and classifying color descriptors for each patch and performing a final post-processing stage to improve segmentation quality. A method for automatic horizon line detection is also proposed. The performance of our approach was evaluated on flight images captured onboard UAVs, achieving performance accuracies above 93% at real-time frame rates.
International
Si
Congress
International Conference on Unmanned Aircraft Systems (ICUAS), 2016
960
Place
Arlington, VA USA
Reviewers
Si
ISBN/ISSN
978-1-4673-9334-8
Start Date
07/06/2016
End Date
10/06/2016
From page
8
To page
14
A Real-time Supervised Learning Approach for Sky Segmentation Onboard Unmanned Aerial Vehicles
Participants
  • Autor: Adrián Carrió Fernández (UPM)
  • Autor: Carlos Sampedro Perez (UPM)
  • Autor: Fu Changhong . (UPM)
  • Autor: Pascual Campoy Cervera (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Visión por Computador y Robótica Aérea
  • Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
  • Departamento: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
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