Talks and Poster Presentations (with Proceedings-Entry):
S. de Sousa, N. Artner, W. Kropatsch:
"On the Evaluation of Graph Centrality for Shape Matching";
Talk: GbR 2013, 9th IAPR - TC-15 Workshop,
- 2013-05-17; in: "Graph-based Representations in Pattern Recognition, 9th IAPR - TC-15 Workshop",
Lecture Notes in Computer Science, Volume 7877, Springer-Verlag,
Graph centrality has been extensively applied in Social Net-
work Analysis to model the interaction of actors and the information ow
inside a graph. In this paper, we investigate the usage of graph centrali-
ties in the Shape Matching task. We create a graph-based representation
of a shape and describe this graph by using di erent centrality measures.
We build a Naive Bayes classi er whose input feature vector consists of
the measurements obtained by the centralities and evaluate the di erent
performances for each centrality
Created from the Publication Database of the Vienna University of Technology.