PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Orientation invariant 3D object classification using hough transform based methods
J Knopp, M Prasad and Luc Van Gool
In: International workshop on 3D Object Retrieval - 3DOR’10, 25-29 October 2010, Florence, Italy.


In comparison to the 2D case, object class recognition in 3D is a much less researched area. However, with the advent of aordable 3D acquisition technology and the growing pop- ularity of 3D content, its relevance is steadily increasing. Just as in the 2D case, 3D data is often partial, noisy and without prior segmentation. Moreover, the object is rarely observed in a canonical frame of reference with respect to orientation (or scale). We propose a method, using Hough- voting for local 3D features, which is orientation (and scale) invariant.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:7981
Deposited By:Luc Van Gool
Deposited On:17 March 2011