[Back]

S. de Sousa, W. Kropatsch:
"The minimum spanning tree of maximum entropy";
Talk: OAGM/AAPR Workshop 2015, Salzburg; 2015-05-28 - 2015-05-29; in: "Proceedings of the ÖAGM Workshop 2015, Salzburg, Austria, May 2015", (2015), Paper ID arXiv:1505.06319 [cs.CV], 7 pages.

In computer vision, we have the problem of creating graphs
out of unstructured point-sets, i.e. the data graph. A common approach
for this problem consists of building a triangulation which might not al-
ways lead to the best solution. Small changes in the location of the points
might generate graphs with unstable configurations and the topology of
the graph could change significantly. After building the data-graph, one
could apply Graph Matching techniques to register the original point-sets.
In this paper, we propose a data graph technique based on the Minimum
Spanning Tree of Maximum Entropty (MSTME). We aim at a data graph
construction which could be more stable than the Delaunay triangula-
tion with respect to small variations in the neighborhood of points. Our
technique aims at creating data graphs which could help the point-set reg-
istration process. We propose an algorithm with a single free parameter
that weighs the importance between the total weight cost and the entropy
of the current spanning tree. We compare our algorithm on a number of
different databases with the Delaunay triangulation.

http://publik.tuwien.ac.at/files/PubDat_243314.pdf