Reconstructing persistent graph structures from noisy images
26th March 2013, 16:00, G12
Dr. Vitaliy Kurlin
Department of Mathematical Sciences,
Let a point cloud be a noisy dotted image of a graph on the plane. We present a new fast algorithm for reconstructing the original graph from the given point cloud. Degrees of vertices in the graph are found by methods of persistent topology. Necessary parameters are automatically optimized by machine learning tools. The algorithm is implemented in the Java applet at
This is a joint work with A.Chernov, which has been recently presented at
DGCI 2013 (Discrete Geometry for Computer Imagery).
The research was supported by the EPSRC grant (EP/I030328/1).