Incremental learning for interactive sketch recognition

Abstract : In this paper, we present the integration of a classifier, based on an incremental learning method, in an interactive sketch analyzer. The classifier recognizes the symbol with a degree of confidence. Sometimes the analyzer considers that the response is insufficient to make the right decision. The decision process then solicits the user to explicitly validate the right decision. The user associates the symbol to an existing class, to a newly created class or ignores this recognition. The classifier learns during the interpretation phase. We can thus have a method for auto-evolutionary interpretation of sketches. In fact, the user participation has a great impact to avoid error accumulation during the analysis. This paper demonstrates this integration in an interactive method based on a competitive breadth-first exploration of the analysis tree for interpreting the 2D architectural floor plans.
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Communication dans un congrès
Ninth IAPR International Workshop on Graphics RECognition, Sep 2011, Séoul, South Korea. 2011
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Dernière modification le : jeudi 5 avril 2018 - 12:30:15
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  • HAL Id : hal-00646137, version 1

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Achraf Ghorbel, Abdullah Almaksour, Aurélie Lemaitre, Eric Anquetil. Incremental learning for interactive sketch recognition. Ninth IAPR International Workshop on Graphics RECognition, Sep 2011, Séoul, South Korea. 2011. 〈hal-00646137〉

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