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What and Who
Title:Homologically Persistent Skeleton in Computer Vision and beyond
Speaker:Vitaliy Kurlin
coming from:Durham University, UK
Speakers Bio:
Event Type:AG1 Mittagsseminar (own work)
Visibility:D1, D2, D3, D4, D5, RG1, SWS, MMCI
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Level:MPI Audience
Date, Time and Location
Date:Tuesday, 19 May 2015
Duration:30 Minutes
Building:E1 4
2D images often contain irregular salient features and interest points with non-integer coordinates. Our skeletonization problem for such a noisy sparse cloud is to summarize the topology of a given 2D cloud across all scales in the form of a graph, which can be used for combining local features into a more powerful object-wide descriptor.

We extend a classical Minimum Spanning Tree of a cloud to the new fundamental concept of a Homologically Persistent Skeleton, which is scale-and-rotation invariant and depends only on the given cloud without extra parameters. This graph
(1) is computable in time O(n log n) for any n points in the plane;
(2) has the minimum total length among all graphs that span a 2D cloud at any scale and also have most persistent 1-dimensional cycles;
(3) is geometrically stable for noisy samples around planar graphs.

The preprint is at

Name(s):Michael Kerber
Video Broadcast
Video Broadcast:NoTo Location:
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  • Michael Kerber, 03/26/2015 03:03 PM -- Created document.