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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Efficient Tensor Voting with 3D tensorial harmonics
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Marco Reisert, Albert Ludwig University, Georges Köhler Allee 52, 79110 Freiburg, Germany
Hans Burkhardt, Albert Ludwig University, Georges Köhler Allee 52, 79110 Freiburg, Germany
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, Hans Burkhardt, "Efficient Tensor Voting with 3D tensorial harmonics," cvprw, pp.1-7, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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