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2D-Line-Drawing-Based 3D Object Recognition

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Part of the Lecture Notes in Computer Science book series (LNIP,volume 7633)

Abstract

3D object recognition has attracted considerable research in computer vision and computer graphics. In this paper, we draw attentions from neurophysiological research that line drawings trigger a neural response similar to natural color images, and propose a line-drawing-based 3D object recognition method. The contribution of the proposed method includes a feature defined for line drawings and a similarity metric for object recognition. Experimental results on McGill 3D shape benchmark show that the proposed method has the best performance when compared to five classic 3D object recognition methods.

Keywords

  • Object Recognition
  • Line Drawing
  • Black Pixel
  • Feature Histogram
  • Good Recognition Performance

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© 2012 Springer-Verlag Berlin Heidelberg

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Liu, YJ., Fu, QF., Liu, Y., Fu, XL. (2012). 2D-Line-Drawing-Based 3D Object Recognition. In: Hu, SM., Martin, R.R. (eds) Computational Visual Media. CVM 2012. Lecture Notes in Computer Science, vol 7633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34263-9_19

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  • DOI: https://doi.org/10.1007/978-3-642-34263-9_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34262-2

  • Online ISBN: 978-3-642-34263-9

  • eBook Packages: Computer ScienceComputer Science (R0)