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Fusing Color and Shape for Bag-of-Words Based Object Recognition

  • Joost van de Weijer
  • Fahad Shahbaz Khan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7786)

Abstract

In this article we provide an analysis of existing methods for the incorporation of color in bag-of-words based image representations. We propose a list of desired properties on which bases fusing methods can be compared. We discuss existing methods and indicate shortcomings of the two well-known fusing methods, namely early and late fusion. Several recent works have addressed these shortcomings by exploiting top-down information in the bag-of-words pipeline: color attention which is motivated from human vision, and Portmanteau vocabularies which are based on information theoretic compression of product vocabularies. We point out several remaining challenges in cue fusion and provide directions for future research.

Keywords

object recognition color features bag-of-words image classification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Joost van de Weijer
    • 1
  • Fahad Shahbaz Khan
    • 2
  1. 1.Computer Vision Center BarcelonaEdifici O, Campus UABBellaterraSpain
  2. 2.Computer Vision LaboratoryLinköping UniversitySweden

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