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Efficient monocular pose estimation for complex 3D models

Author
Rubio, A.; Villamizar, M.A.; Ferraz, L.; Peñate, A.; Ramisa, A.; Simo, E.; Sanfeliu, A.; Moreno-Noguer, F.
Type of activity
Presentation of work at congresses
Name of edition
2015 IEEE International Conference on Robotics and Automation
Date of publication
2015
Presentation's date
2015
Book of congress proceedings
2015 IEEE International Conference on Robotics and Automation (ICRA 2015): Seattle, Washington, USA, 26-30 May 2015
First page
1397
Last page
1402
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
https://doi.org/10.1109/ICRA.2015.7139372 Open in new window
Project funding
DPI2011-27510 Perception and Action in Robotics Problems with Large State Spaces
FP7-ICT- 287617 Aerial Robotics Cooperative Assembly System
Robot-Human interaction, learning and cooperation in urban areas
Visual Sense, Tagging visual data with semantic descriptions PCIN-2013-047
Repository
http://hdl.handle.net/2117/83560 Open in new window
URL
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7139372 Open in new window
Abstract
We propose a robust and efficient method to estimate the pose of a camera with respect to complex 3D textured models of the environment that can potentially contain more than 100, 000 points. To tackle this problem we follow a top down approach where we combine high-level deep network classifiers with low level geometric approaches to come up with a solution that is fast, robust and accurate. Given an input image, we initially use a pre-trained deep network to compute a rough estimation of the c...
Citation
Rubio, A., Villamizar, M.A., Ferraz, L., Peñate, A., Ramisa, A., Simo, E., Sanfeliu, A., Moreno-Noguer, F. Efficient monocular pose estimation for complex 3D models. A: IEEE International Conference on Robotics and Automation. "2015 IEEE International Conference on Robotics and Automation (ICRA 2015): Seattle, Washington, USA, 26-30 May 2015". Seattle, WA: Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 1397-1402.
Keywords
complex 3D models, computer vision, deep learning, pose estimation; camera pose estimation
Group of research
ROBiri - IRI Robotics Group
VIS - Artificial Vision and Intelligent Systems

Participants

  • Rubio Romano, Antonio  (author and speaker )
  • Villamizar Vergel, Michael Alejandro  (author and speaker )
  • Ferraz Colomina, Luis  (author and speaker )
  • Peñate Sánchez, Adrián  (author and speaker )
  • Ramisa Ayats, Arnau  (author and speaker )
  • Simo Serra, Edgar  (author and speaker )
  • Sanfeliu Cortes, Alberto  (author and speaker )
  • Moreno Noguer, Francesc d'Assis  (author and speaker )