@article{3781,
abstract = {We bound the difference in length of two curves in terms of their total curvatures and the Fréchet distance. The bound is independent of the dimension of the ambient Euclidean space, it improves upon a bound by Cohen-Steiner and Edelsbrunner, and it generalizes a result by Fáry and Chakerian.},
author = {Fasy, Brittany Terese},
journal = {Acta Sci. Math. (Szeged)},
number = {1-2},
pages = {359 -- 367},
publisher = {Szegedi Tudományegyetem},
title = {{The difference in length of curves in R^n}},
volume = {77},
year = {2011},
}
@inbook{3796,
abstract = {We address the problem of covering ℝ n with congruent balls, while minimizing the number of balls that contain an average point. Considering the 1-parameter family of lattices defined by stretching or compressing the integer grid in diagonal direction, we give a closed formula for the covering density that depends on the distortion parameter. We observe that our family contains the thinnest lattice coverings in dimensions 2 to 5. We also consider the problem of packing congruent balls in ℝ n , for which we give a closed formula for the packing density as well. Again we observe that our family contains optimal configurations, this time densest packings in dimensions 2 and 3.},
author = {Edelsbrunner, Herbert and Kerber, Michael},
booktitle = {Rainbow of Computer Science},
editor = {Calude, Cristian and Rozenberg, Grzegorz and Salomaa, Arto},
pages = {20 -- 35},
publisher = {Springer},
title = {{Covering and packing with spheres by diagonal distortion in R^n}},
doi = {10.1007/978-3-642-19391-0_2},
volume = {6570},
year = {2011},
}
@inproceedings{3782,
abstract = {In cortex surface segmentation, the extracted surface is required to have a particular topology, namely, a two-sphere. We present a new method for removing topology noise of a curve or surface within the level set framework, and thus produce a cortical surface with correct topology. We define a new energy term which quantifies topology noise. We then show how to minimize this term by computing its functional derivative with respect to the level set function. This method differs from existing methods in that it is inherently continuous and not digital; and in the way that our energy directly relates to the topology of the underlying curve or surface, versus existing knot-based measures which are related in a more indirect fashion. The proposed flow is validated empirically.},
author = {Chen, Chao and Freedman, Daniel},
booktitle = { Conference proceedings MCV 2010},
location = {Beijing, China},
pages = {31 -- 42},
publisher = {Springer},
title = {{Topology noise removal for curve and surface evolution}},
doi = {10.1007/978-3-642-18421-5_4},
volume = {6533},
year = {2010},
}
@inbook{3795,
abstract = {The (apparent) contour of a smooth mapping from a 2-manifold to the plane, f: M → R2 , is the set of critical values, that is, the image of the points at which the gradients of the two component functions are linearly dependent. Assuming M is compact and orientable and measuring difference with the erosion distance, we prove that the contour is stable.},
author = {Edelsbrunner, Herbert and Morozov, Dmitriy and Patel, Amit},
booktitle = {Topological Data Analysis and Visualization: Theory, Algorithms and Applications},
pages = {27 -- 42},
publisher = {Springer},
title = {{The stability of the apparent contour of an orientable 2-manifold}},
doi = {10.1007/978-3-642-15014-2_3},
year = {2010},
}
@inproceedings{3848,
abstract = {We define the robustness of a level set homology class of a function f:XR as the magnitude of a perturbation necessary to kill the class. Casting this notion into a group theoretic framework, we compute the robustness for each class, using a connection to extended persistent homology. The special case X=R3 has ramifications in medical imaging and scientific visualization.},
author = {Bendich, Paul and Edelsbrunner, Herbert and Morozov, Dmitriy and Patel, Amit},
location = {Liverpool, UK},
pages = {1 -- 10},
publisher = {Springer},
title = {{The robustness of level sets}},
doi = {10.1007/978-3-642-15775-2_1},
volume = {6346},
year = {2010},
}