Riemannian level-set methods for tensor-valued data

Details Riemannian level-set methods for tensor-valued data Riemannian level-set methods for tensor-valued data

2007-05-02

arxiv.org/abs/0705.0214v1

Computer Science

Computer Vision and Pattern Recognition

11 pages, 03 figures, to be published in the proceedings of SSVM 2007, LNCS Springer

Scientific paper

We present a novel approach for the derivation of PDE modeling
curvature-driven flows for matrix-valued data. This approach is based on the
Riemannian geometry of the manifold of Symmetric Positive Definite Matrices
Pos(n).

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