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  4. Combining Visible and Near-Infrared Cues for Image Categorisation
 
conference paper

Combining Visible and Near-Infrared Cues for Image Categorisation

Salamati, Neda  
•
Larlus, Diane
•
Csurka, Gabriela
2011
Proc. of the 22nd British Machine Vision Conference (BMVC 2011).
22nd British Machine Vision Conference (BMVC 2011)

Standard digital cameras are sensitive to radiation in the near-infrared domain, but this additional cue is in general discarded. In this paper, we consider the scene categorisation problem in the context of images where both standard visible RGB channels and near infrared information are available. Using efficient local patch-based Fisher Vector image representations, we show based on thorough experimental studies the benefit of using this new type of data. We investigate which image descriptors are relevant, and how to best combine them. In particular, our experiments show that when combining texture and colour information, computed on visible and near-infrared channels, late fusion is the best performing strategy and outperforms the state-of-the-art categorisation methods on RGB-only data.

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Type
conference paper
DOI
10.5244/C.25.49
Author(s)
Salamati, Neda  
Larlus, Diane
Csurka, Gabriela
Date Issued

2011

Published in
Proc. of the 22nd British Machine Vision Conference (BMVC 2011).
Subjects

Image classification

•

Near-infrared imaging

•

Fisher vector

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
IVRL  
Event nameEvent placeEvent date
22nd British Machine Vision Conference (BMVC 2011)

Dundee, Scotland.

30 August - 1 September, 2011

Available on Infoscience
October 10, 2011
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/71482
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