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Alicia Fornes, Josep Llados and Gemma Sanchez. 2007. Old Handwritten Musical Symbol Classification by a Dynamic Time Warping Based Method. Seventh IAPR International Workshop on Graphics Recognition.26–27.
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Jose Antonio Rodriguez, Gemma Sanchez and Josep Llados. 2007. Categorization of Digital Ink Elements using Spectral Features. Seventh IAPR International Workshop on Graphics Recognition.63–64.
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Ernest Valveny, Salvatore Tabbone, Oriol Ramos Terrades and Emilie Jean-Marie Odile. 2007. Performance Characterization of Shape Descriptors for Symbol Representation. Seventh IAPR International Workshop on Graphics Recognition.82–83.
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Alicia Fornes, Sergio Escalera, Josep Llados and Gemma Sanchez. 2007. Symbol Recognition by Multi-class Blurred Shape Models. Seventh IAPR International Workshop on Graphics Recognition.11–13.
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Liu Wenyin, Josep Llados and Jean-Marc Ogier. 2008. Graphics Recognition. Recent Advances and New Opportunities.. (LNCS.)
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Alicia Fornes, Josep Llados, Gemma Sanchez and Horst Bunke. 2009. Symbol-independent writer identification in old handwritten music scores. In proceedings of 8th IAPR International Workshop on Graphics Recognition. Springer Berlin Heidelberg, 186–197.
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S. Jouili, Salvatore Tabbone and Ernest Valveny. 2009. Evaluation of graph matching measures for documents retrieval. In proceedings of 8th IAPR International Workshop on Graphics Recognition.13–21.
Abstract: In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used which include line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each grahp distance measure depends on the kind of data and the graph representation technique.
Keywords: Graph Matching; Graph retrieval; structural representation; Performance Evaluation
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Joan Mas, Gemma Sanchez and Josep Llados. 2009. SSP: Sketching slide Presentations, a Syntactic Approach. 8th IAPR International Workshop on Graphics Recognition.
Abstract: The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide.
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S.Jouili, Salvatore Tabbone and Ernest Valveny. 2009. Comparing Graph Similarity Measures for Graphical Recognition. 8th IAPR International Workshop on Graphics Recognition. Springer. (LNCS.)
Abstract: In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique.
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Mathieu Nicolas Delalandre, Jean-Yves Ramel, Ernest Valveny and Muhammad Muzzamil Luqman. 2009. A Performance Characterization Algorithm for Symbol Localization. 8th IAPR International Workshop on Graphics Recognition. Springer, 3–11.
Abstract: In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).
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