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Multiscale combinatorial grouping

Author
Arbelaez, P.; Pont, J.; Barron, J.; Marques, F.; Malik, J.
Type of activity
Presentation of work at congresses
Name of edition
IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2014
Date of publication
2014
Presentation's date
2014-06
Book of congress proceedings
2014 IEEE Conference on Computer Vision and Pattern Recognition, 23-28 June 2014, Columbus, Ohio: proceedings
First page
328
Last page
335
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
https://doi.org/10.1109/CVPR.2014.49 Open in new window
Repository
http://hdl.handle.net/2117/26949 Open in new window
URL
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6909443 Open in new window
Abstract
We propose a unified approach for bottom-up hierarchical image segmentation and object candidate generation for recognition, called Multiscale Combinatorial Grouping (MCG). For this purpose, we first develop a fast normalized cuts algorithm. We then propose a high-performance hierarchical segmenter that makes effective use of multiscale information. Finally, we propose a grouping strategy that combines our multiscale regions into highly-accurate object candidates by exploring efficiently their c...
Citation
Arbelaez, P. [et al.]. Multiscale combinatorial grouping. A: IEEE Conference on Computer Vision and Pattern Recognition. "2014 IEEE Conference on Computer Vision and Pattern Recognition, 23-28 June 2014, Columbus, Ohio: proceedings". Columbus, Ohio: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 328-335.
Keywords
Image Segmentation, Object Candidates
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants

  • Arbelaez, Pablo Andres  (author and speaker )
  • Pont Tuset, Jordi  (author and speaker )
  • Barron, Jonathan  (author and speaker )
  • Marques Acosta, Fernando  (author and speaker )
  • Malik, Jitendra  (author and speaker )

Attachments