Diffusion runs low on persistence fast Conference Poster

Author(s): Chen, Chao; Edelsbrunner, Herbert
Title: Diffusion runs low on persistence fast
Affiliation IST Austria
Abstract: Interpreting an image as a function on a compact sub- set of the Euclidean plane, we get its scale-space by diffu- sion, spreading the image over the entire plane. This gener- ates a 1-parameter family of functions alternatively defined as convolutions with a progressively wider Gaussian ker- nel. We prove that the corresponding 1-parameter family of persistence diagrams have norms that go rapidly to zero as time goes to infinity. This result rationalizes experimental observations about scale-space. We hope this will lead to targeted improvements of related computer vision methods.
Conference Title: ICCV: International Conference on Computer Vision
Conference Dates: November 6-13, 2011
Conference Location: Barcelona, Spain
Publisher: IEEE  
Date Presented: 2011-11-06
Start Page: 423
End Page: 430
DOI: 10.1109/ICCV.2011.6126271
Open access: yes (repository)
IST Austria Authors
  1. Chao Chen
    14 Chen
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