ExpressMatch: A System for Creating Ground-Truthed Datasets of Online Mathematical Expressions

Aguilar, Frank Dennis Julca; Hirata, Nina S. T.

doi:10.1109/das.2012.38

Cited by 12 publications

(11 citation statements)

References 9 publications

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“…For Part 4, the training data includes thousands of expressions from existing handwritten expression datasets, including (i) MathBrush (University of Waterloo) [18], (ii) HAMEX (University of Nantes) [19], (iii) MfrDB (Czech Technical University) [5], (iv) ExpressMatch (University of Sao Paulo) [20] and (v) the KAIST dataset. Due to differences in legal symbols and layouts, not all expressions in these data sets were consistent with the Part 4 grammar.…”

Section: A Datasets and Expression Encodingsmentioning

confidence: 99%

ICDAR 2013 CROHME: Third International Competition on Recognition of Online Handwritten Mathematical Expressions

Mouchère

Viard-Gaudin

Zanibbi

et al. 2013

2013 12th International Conference on Document Analysis and Recognition

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Abstract-We report on the third international Competition on Handwritten Mathematical Expression Recognition (CROHME), in which eight teams from academia and industry took part. For the third CROHME, the training dataset was expanded to over 8000 expressions, and new tools were developed for evaluating performance at the level of strokes as well as expressions and symbols. As an informal measure of progress, the performance of the participating systems on the CROHME 2012 data set is also reported. Data and tools used for the competition will be made publicly available.

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Section: A Datasets and Expression Encodingsmentioning

confidence: 99%

ICDAR 2013 CROHME: Third International Competition on Recognition of Online Handwritten Mathematical Expressions

Mouchère

Viard-Gaudin

Zanibbi

et al. 2013

2013 12th International Conference on Document Analysis and Recognition

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“…Structural analysis is performed by recursively extracting baselines [9], using contextual constraints to guide the selection of symbols on a baseline. In addition to the CROHME dataset, the system has been trained using samples from the ExpressMatch dataset [10]. The ExpressMatch dataset is composed of 468 expressions and a total of 5600 symbols.…”

Section: System Descriptionsmentioning

confidence: 99%

“…Training and test data for CROHME 2012 along with related tools were available from the International Association of Pattern Recognition (IAPR) 4 . For Part 4, the training data includes thousands of expressions from existing handwritten expression datasets, including (i) MathBrush (University of Waterloo) [18], (ii) HAMEX (University of Nantes) [19], (iii) MfrDB (Czech Technical University) [5], (iv) ExpressMatch (University of Sao Paulo) [20] and (v) the KAIST dataset. Due to differences in legal symbols and layouts, not all expressions in these data sets were consistent with the Part 4 grammar.…”

Section: A Datasets and Expression Encodingsmentioning

confidence: 99%

The Problem of Handwritten Mathematical Expression Recognition Evaluation

Awal¹,

Mouchère²,

Viard-Gaudin³

2010

2010 12th International Conference on Frontiers in Handwriting Recognition

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“…• foi desenvolvido um software juntamente com o aluno Frank D. J. Aguilar [1], denominado ExpressMatch, que possibilita a denição de expressões modelo, coleta de amostras por meio de transcrições das expressões modelo, a anotação dos símbolos usando o método de casamento proposto, correção da anotação e a exportação do conjunto de símbolos para um arquivo. A coleta das expressões de um dos conjuntos de dados utilizados neste trabalho foi realizada com esse software;…”

Section: Principais Contribuições E Resultadosunclassified

“…Para a coleta do conjunto de dados B, utilizou-se o programa ExpressMatch [1] em um tablet PC HP Pavilion tx2500, com 12.1 polegadas e uma resolução de 1280 × 800 pixels.…”

Section: 12unclassified

Rotulação de símbolos matemáticos manuscritos via casamento de expressões

Honda¹

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The problem of recognizing handwritten mathematical expressions includes three important subproblems: symbol segmentation, symbol recognition, and structural analysis of expressions. In order to evaluate recognition methods and techniques, they should be tested on representative sample sets of the application domain. One of the concerns that are being repeatedly pointed recently is the almost non-existence of public representative datasets of mathematical expressions, which makes dicult the development and comparison of distinct approaches. In general, recognition results reported in the literature are restricted to small datasets, not publicly available, and often consisting of data aiming only evaluation of some specic aspects of the recognition. In the case of online expressions, to train and test symbol recognizers, samples are in general obtained asking users to write a series of symbols individually and repeatedly. Such task is boring and tiring. An alternative approach for obtaining samples of symbols would be to ask users to transcribe previously dened model expressions. By doing so, writing would be more natural and less boring, and several symbol samples could be obtained from one transcription. To avoid the task of manually labeling the symbols of the transcribed expressions, in this work a method for handwritten expression matching, in which symbols of a transcribed expression are assigned to the corresponding ones in the model expression, is proposed. The proposed method is based on a formulation that reduces the matching problem to a linear assignment problem, where costs are dened based on symbol features and expression structure. Experimental results using the proposed method show that mean correct assignment rate superior to 99% is achieved.

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ExpressMatch: A System for Creating Ground-Truthed Datasets of Online Mathematical Expressions

Cited by 12 publications

References 9 publications

ICDAR 2013 CROHME: Third International Competition on Recognition of Online Handwritten Mathematical Expressions

ICDAR 2013 CROHME: Third International Competition on Recognition of Online Handwritten Mathematical Expressions

The Problem of Handwritten Mathematical Expression Recognition Evaluation

Rotulação de símbolos matemáticos manuscritos via casamento de expressões

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