Sketchable Histograms of Oriented Gradients for Object Detection

  • Ekaterina Zaytseva
  • Santi Seguí
  • Jordi Vitrià
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7441)


In this paper we investigate a new representation approach for visual object recognition. The new representation, called sketchable-HoG, extends the classical histogram of oriented gradients (HoG) feature by adding two different aspects: the stability of the majority orientation and the continuity of gradient orientations. In this way, the sketchable-HoG locally characterizes the complexity of an object model and introduces global structure information while still keeping simplicity, compactness and robustness. We evaluated the proposed image descriptor on publicly Catltech 101 dataset. The obtained results outperforms classical HoG descriptor as well as other reported descriptors in the literature.


Object Recognition Feature stability Centrality measures Histogram of Oriented Gradients 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ekaterina Zaytseva
    • 1
  • Santi Seguí
    • 1
    • 2
  • Jordi Vitrià
    • 1
    • 2
  1. 1.Computer Vision CenterUniversitat Autònoma de BarcelonaSpain
  2. 2.Dept. de Matemàtica Aplicada i AnàlisiUniversitat de BarcelonaSpain

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