Abstract
These proceedings present the papers accepted for the 9th IAPR-TC-15 Work-shop on Graph-based Representations in Pattern Recognition (GbR) 2013. Formore than 15 years, GbR has been providing a forum for researchers from thefields of pattern recognition, image processing, and computer vision who buildtheir works on the basis of graph theory. This year it was a great pleasure for usto organize the GbR 2013 in the heart of Europe - Vienna, Austria.The Technical Committee 15 (TC15) of the International Association forPattern Recognition (IAPR) was created in 1996. It encourages elaboration ofgraph-based research works, is an integral partner in organizing biennial GbRworkshops, sponsors related special sessions at conferences, and promotes specialissues in journals.Traditionally the work presented at GbR covers a wide range of topics. Thescope of the papers varies from theoretical contributions to applications, fromdiscovering the new properties of a single graph (graph edit distance, maximumcut, graph characteristics derived from Schr ̈odinger equation) to developing al-gorithms for sets of graphs, maximum subgraph problems and graph matching.A great interest was shown in the problems of graph kernels and topology.Besides the regular research papers, this workshop featured two highlights:the IAPR distinguished speakers Mario Vento and Herbert Edelsbrunner. MarioVento was among the founders of TC15 some 16 years ago. He summarized thedevelopment of our field starting with the original motivation. It allowed theyounger generation of our community to compare the goals and expectationsof the early years with the current state. Herbert Edelsbrunner created a newbridge from TC15 to the area of topology and persistence.Overall, GbR 2013 attracted 27 submissions from 10 countries. Each paperwent through a critical reviewing process by at least two members of the inter-national Program Committee. Finally, 24 papers including the contributions ofthe invited speakers were accepted for oral presentation and publication in theseproceedings.On behalf of the organizers, we would like to thank the members of theProgram Committee for their timely and competent reviews; the authors of thesubmitted papers for their work and their abidance to all deadlines. Finally,we would like to thank the IAPR for sponsoring our workshop and the IAPRdistinguished speakers for their contributions.
Reference
Graph-Based Representations in Pattern Recognition. (2013). In W. Kropatsch, N. Artner, Y. Haxhimusa, & X. Jiang (Eds.), Lecture Notes in Computer Science. Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-642-38221-5