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Incremental Learning for Interactive Sketch Recognition

  • Conference paper
Graphics Recognition. New Trends and Challenges (GREC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7423))

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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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Ghorbel, A., Almaksour, A., Lemaitre, A., Anquetil, E. (2013). Incremental Learning for Interactive Sketch Recognition. In: Kwon, YB., Ogier, JM. (eds) Graphics Recognition. New Trends and Challenges. GREC 2011. Lecture Notes in Computer Science, vol 7423. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36824-0_11

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  • DOI: https://doi.org/10.1007/978-3-642-36824-0_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36823-3

  • Online ISBN: 978-3-642-36824-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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