Talks and Poster Presentations (with Proceedings-Entry):

C. Chen, H. Edelsbrunner:
"Diffusion runs low on persistence fast";
Talk: 13th IEEE International Conference on Computer Vision, Barcelona, Spanien; 2011-11-06 - 2011-11-13; in: "13th IEEE International Conference on Computer Vision", (2011), 1 - 8.

English abstract:
Interpreting an image as a function on a compact subset of
the Euclidean plane, we get its scale-space by diffusion,
spreading the image over the entire plane. This generates
a 1-parameter family of functions alternatively deï ned
as convolutions with a progressively wider Gaussian kernel.
We prove that the corresponding 1-parameter family of
persistence diagrams have norms that go rapidly to zero as
time goes to inï nity. This result rationalizes experimental
observations about scale-space. We hope this will lead to
targeted improvements of related computer vision methods.

Created from the Publication Database of the Vienna University of Technology.