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Multi-Criteria Handwriting Quality Analysis with Online Fuzzy Models

Abstract : IntuiScript is an innovative project aiming at the development of a digital workbook providing feedback during the handwriting learning process for children from three to seven years old. In this context, the paper presents a method to analyse handwriting quality that responds to the expectations of the IntuiScript educational scenario: on-line and real time feedback for children, an automatic detection of children mistakes guiding the pedagogical progression, and a precise analysis of children writing saved to help teacher to understand children writing skills. The presented method introduces a multi-criteria architecture to analyse handwriting quality based on three different aspects: shape, order and direction. The validation of the proposed approach is done on a realistic dataset collected in preschools and primary schools with 952 children. Results show a positive feedback of children and teachers about the use of tactile digital devices, and a significant improvement of the performances of the multi-criteria architecture compared to the previous analyser. The ground truth has been annotated by experts with different levels of confidence. Specific evaluation metrics are introduced to deal with confidence annotations.
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Submitted on : Thursday, April 27, 2017 - 2:19:17 PM
Last modification on : Wednesday, November 3, 2021 - 6:05:49 AM
Long-term archiving on: : Friday, July 28, 2017 - 1:01:17 PM


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Damien Simonnet, Eric Anquetil, Manuel Bouillon. Multi-Criteria Handwriting Quality Analysis with Online Fuzzy Models. Pattern Recognition, Elsevier, 2017, 69, pp.310-324. ⟨10.1016/j.patcog.2017.04.003⟩. ⟨hal-01515397⟩



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