Automatic learning of symbol descriptions avoiding topological ambiguities

Authors:
J. Mas;B. Lamiroy;G. Sanchez;J. Llados
Affiliations:
Computer Vision Center, Computer Science Dept., UAB, Spain;INPL-LORIA, Ecole des Mines, Nancy Cedex, France;Computer Vision Center, Computer Science Dept., UAB, Spain;Computer Vision Center, Computer Science Dept., UAB, Spain
Venue:
SBM'06 Proceedings of the Third Eurographics conference on Sketch-Based Interfaces and Modeling
Year:
2006

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Abstract

In this paper we address both automatic recognition of sketched symbols and the construction of the corresponding models from user drawn examples. Our approach is based on a two stage process. In a first phase we use an Adjacency Grammar to express topological properties of the symbol. In order to be able to further disambiguate topologically similar configurations on the rules of the grammar that are triggered by the recognition process produce a set of local geometric invariants is defined. The combination of both steps results in an efficient recognition method for user drawn sketches. Furthermore, we show that the same approach can easily be adapted for the generation of Adjacency Grammars from user provided and hand drawn examples.