Memorias de investigación
Ponencias en congresos:
Visual Model Feature Tracking for UAV Control
Año:2007

Áreas de investigación
  • Automática

Datos
Descripción
This paper explores the possibilities to use robust object tracking algorithms based on visual model features as generator of visual references for UAV control. A Scale Invariant Feature Transform (SIFT) algorithm is used for detecting the salient points at every processed image, then a projective transformation for evaluating the visual references is obtained using a version of the RANSAC algorithm, in which a series of matched key-points pairs that fulfill the transformation equations are selected, rejecting otherwise the corrupted data. The system has been tested using diverse image sequences showing its capability to track objects significantly changed in scale, position, rotation, generating at the same time velocity references to the UAV flight controller. The robustness our approach has also been validated using images taken from real flights showing noise and lighting distortions. The results presented are promising in order to be used as reference generator for the control system.controller which is responsible for autonomous control of the helicopter.
Internacional
Si
Nombre congreso
5th IEEE International Symposium on Intelligent Signal Processing; WISP2007
Tipo de participación
960
Lugar del congreso
Alcala de Henares
Revisores
Si
ISBN o ISSN
1-4244-0830-X/07
DOI
Fecha inicio congreso
03/10/2007
Fecha fin congreso
05/10/2007
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Título de las actas

Esta actividad pertenece a memorias de investigación

Participantes
  • Participante: Juan Fernando Correa Caicedo
  • Autor: Pascual Campoy Cervera UPM
  • Participante: Ivan Fernando Mondragón Bernal
  • Autor: Luis Mejías . UPM

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Visión por computador
  • Departamento: Automática, Ingeniería Electrónica e Informática Industrial