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Anchorage, AK, USA
June 23, 2008 to June 28, 2008
ISBN: 978-1-4244-2339-2
pp: 1-7
Marco Reisert , Albert Ludwig University, Georges Köhler Allee 52, 79110 Freiburg, Germany
ABSTRACT
Tensor Voting is a robust technique to extract low-level features in noisy images. The approach achieves its robustness by exploiting coherent orientations in local neighborhoods. In this paper we propose an efficient algorithm for dense Tensor Voting in 3D which makes use of steerable filters. Therefore, we propose steerable expansions of spherical tensor fields in terms of tensorial harmonics, which are their canonical representation. In this way it is possible to perform arbitrary rank Tensor Voting by linear-combinations of convolutions in an efficient way.
CITATION
Marco Reisert, "Efficient Tensor Voting with 3D tensorial harmonics", CVPRW, 2008, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops 2008, pp. 1-7, doi:10.1109/CVPRW.2008.4562962
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