Éditeur(s) : HAL CCSD
Résumé : International audience
We propose in this paper a new online Multi-UserMulti-Touch handwritten diagram DataBase (MUMTDB) forevaluating recognition systems under the multi-user situation.The data is collected according to two predefined mind mapscenarios which contains 9 classes of graphical symbols. Eachscenario is completed by involving two users at the same time.Since the users are given freedom to draw the symbols asthey want, the dataset contains a diversity of multi-stroke andeven multi-touch symbols. It allows addressing new challengingproblems regarding the recognition of simultaneous composition of structured documents. The dataset is freely availableon-line.
International Conference on Frontiers in Handwriting Recognition (ICFHR)
Shenzhen, China

hal-01374376
https://hal.univ-antilles.fr/hal-01374376

Éditeur(s) : HAL CCSD
Résumé : International audience
In this paper, we present a novel method for recognition of handwritten sketches. Unlike previous approaches, we focus on online retrieval and ability to build our model incrementally, thus we do not need to know all the data in advance and we can achieve very good recognition results after as few as 15 samples. The method is composed of two main parts: feature representation and learning and recognition. In feature representation part, we utilize SIFT-like feature descriptors in combination with soft response Bag-of-Words techniques. Descriptors are extracted locally using our novel sketch-specific sampling strategy and for support regions we follow patch-based approach. For learning and recognition, we use a novel technique based on fuzzy-neural networks, which has shown good performance in incremental learning. The experiments on state-of-the-art benchmarks have shown promising results.
17th Biennial Conference of the International Graphonomics Society
Pointe-à-Pitre, Guadeloupe

hal-01166497
https://hal.univ-antilles.fr/hal-01166497
https://hal.univ-antilles.fr/hal-01166497/document
https://hal.univ-antilles.fr/hal-01166497/file/IGS_2015_submission_37.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
Pen-based interfaces allow users to interact with the help of a stylus and/or fingers. Thanks to a recognition system, users can execute commands by drawing gestures. Because of the complexity of the software, the set of gesture commands can be very large. Consequently, it becomes difficult for the users to remember all the commands. In this paper we introduce "Semicustomizable gestural commands". The idea is to take into account the commands usage frequency: to facilitate the memorization of the most used commands we leave users the freedom/liberty to define their associated gestures (by) themselves. The remaining gesture commands will be automatically generated on the base of the defined gestures according to their hierarchical categorization. Several comparative tests demonstrate that this new approach improved the progressive memorization of the gestural commands.
ICFHR 2012 - International Conference on Frontiers in Handwriting Recognition
Bari, Italy

hal-00708750
https://hal.inria.fr/hal-00708750
https://hal.inria.fr/hal-00708750/document
https://hal.inria.fr/hal-00708750/file/ICFHR_LI_IEEE.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
The large majority of methods proposed in literature for handwriting recognition assume that words are produced drawing large parts of the ink without lifting the pen, other than horizontal bars and dots. This fundamental assumption, however, does not always hold: while some educational systems provide explicit training for producing continuous handwriting, minimizing the number of pen-up during the production of a word, others do not. As a consequence, whenever the handwriting presents pen-up within a word, the recognition performance can drop significantly. In a preliminary study, we presented an algorithm for discriminating among different types of ink appearing in handwriting, namely isolated characters, cursive, dots, horizontal and vertical bars, based on the use of a suitable set of features. In this paper, we have characterized the discriminative power of each considered feature according to different measures and we have proposed a method for combining the different feature rankings. We have also used the Fischer's Linear Discriminant Analysis (LDA) for exhaustively selecting the best feature subsets with increasing number of features. Finally, we have compared the results obtained by using the feature subsets provided by LDA with those obtained with the feature subsets selected according to our feature ranking. The experimental results, on different datasets of handwritten words, showed that our approach successfully achieves its aim allowing to reduce the computational cost without affecting the overall performance of the recognition process.
17th Biennial Conference of the International Graphonomics Society
Pointe-à-Pitre, Guadeloupe

hal-01165877
https://hal.univ-antilles.fr/hal-01165877
https://hal.univ-antilles.fr/hal-01165877/document
https://hal.univ-antilles.fr/hal-01165877/file/IGS_2015_submission_13.pdf

Éditeur(s) : Londres : T. Woolmer
Siècle(s) traité(s) : 19
Provenance : Archives départementales de Guadeloupe
Permalien : http://www.manioc.org/patrimon/ADG18190
ADG18190

Éditeur(s) : HAL CCSD
Résumé : International audience
In this paper, we introduce a framework for on-line learning of handwritten symbols from scratch. As such, learning suffers from missing data at the beginning of the learning process, in this paper we propose the use of Sigma-lognormal model to generate synthetic data. Our framework deals with a real-time use of the system, where the recognition of a single symbol cannot be postponed by the generation of synthetic data. We evaluate the use of our framework and Sigma-lognormal model by comparison of the recognition rate to a block-learning and learning without any synthetic data. Experimental results show that both of these contributions represent an enhancement to the on-line handwriting recognition, especially when starting from scratch.
17th Biennial Conference of the International Graphonomics Society
Pointe-à-Pitre, Guadeloupe

hal-01165923
https://hal.univ-antilles.fr/hal-01165923
https://hal.univ-antilles.fr/hal-01165923/document
https://hal.univ-antilles.fr/hal-01165923/file/IGS_2015_submission_34.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
The advent of pen-based interfaces has led to the development of many applications concerning the analysis of a drawn shape. But a drawing is not only a shape. It is also all the gestures which constitutes the drawing activity, as well as their planning. Pen-based interfaces give us the possibility to analyze this dimension of sketching. We call this kind of analysis: procedural analysis. In this article, we will show how to identify the privileged drawing procedures of users by identifying a constant pattern despite a huge within-drawer variability in drawing procedures. After stating how to extract this constant pattern, we shall show how we can use those results into a drawing-based user identification method.
ICFHR 2012 - International Conference on Frontiers in Handwriting Recognition
Bari, Italy

hal-00708708
https://hal.inria.fr/hal-00708708

Éditeur(s) : HAL CCSD
Résumé : International audience
Drawing and handwriting are communicational skills that are fundamental in geopolitical, ideological and technological evolutions of all time. drawingand handwriting are still useful in defining innovative applications in numerous fields. In this regard, researchers have to solve new problems like those related to the manner in which drawing and handwriting become an efficient way to command various connected objects; or to validate graphomotor skills as evident and objective sources of data useful in the study of human beings, their capabilities and their limits from birth to decline.
17th Biennial Conference of the International Graphonomics Society
Pointe-à-Pitre, Guadeloupe

Droits : http://creativecommons.org/licenses/by-nc-nd/
ISBN : 979-10-95177-01-2
hal-01166509
https://hal.univ-antilles.fr/hal-01166509
https://hal.univ-antilles.fr/hal-01166509/document
https://hal.univ-antilles.fr/hal-01166509/file/IGS2015proceedingsvHal-1.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
The goal of our experiment is to develop a useful and accessible tool that can be used to evaluate a patient's health by analyzing handwritten strokes. We use a cloud computing approach to analyze stroke data sampled on a commercial tablet working on the Android platform and a distant server to perform complex calculations using the Delta and Sigma lognormal algorithms. A Google Drive account is used to store the data and to ease the development of the project. The communication between the tablet, the cloud and the server is encrypted to ensure biomedical information confidentiality. Highly parameterized biomedical tests are implemented on the tablet as well as a free drawing test to evaluate the validity of the data acquired by the first test compared to the second one. A blurred shape model descriptor pattern recognition algorithm is used to classify the data obtained by the free drawing test. The functions presented in this paper are still currently under development and other improvements are needed before launching the application in the public domain.
17th Biennial Conference of the International Graphonomics Society
Pointe-à-Pitre, Guadeloupe

hal-01165890
https://hal.univ-antilles.fr/hal-01165890
https://hal.univ-antilles.fr/hal-01165890/document
https://hal.univ-antilles.fr/hal-01165890/file/IGS_2015_submission_20.pdf

Éditeur(s) : HAL CCSD
Résumé : Best paper for innovative research
International audience
This paper investigates the interest of using the Kinematic Theory of rapid human movements to analyseand evaluate the handwriting produced by young kindergarten children in typical classroom environment. A total of66 children participated in this trial. For the preliminary results reported herein, movements from 15 children, takenevenly from three different levels (3, 4, and 5 years old), were analyzed. Our results confirm that 1) the sigmalognormalequation can model accurately childen’s movement and 2) that this modeling can differentiate betweenchildren of different school levels, hence supporting the relevance of pursuing along this original pathway.
Recent Progress in Graphonomics: Learn from the Past. IGS 2013
Nara, Japan

hal-01098125
https://hal.archives-ouvertes.fr/hal-01098125

Éditeur(s) : HAL CCSD
Résumé : International audience
Extract the features for a multi-touch gesture is difficult due to the complex temporal and motion relations between multiple trajectories. In this paper we present a new generic graph model to quantify the shape, temporal and motion information from multi-touch gesture. To make a comparison between graph, we also propose a specific graph matching method based on graph edit distance. Results prove that our graph model can be fruitfully used for multi-touch gesture pattern recognition purpose with the classifier of graph embedding and SVM.
17th Biennial Conference of the International Graphonomics Society
Pointe-à-Pitre, Guadeloupe

hal-01165768
https://hal.univ-antilles.fr/hal-01165768
https://hal.univ-antilles.fr/hal-01165768/document
https://hal.univ-antilles.fr/hal-01165768/file/IGS_2015_submission_6.pdf

Résumé : Demandes de remboursements à Haïti : message du Président des Etats Unis
Siècle(s) traité(s) : 19
Droits : Domaine public
Provenance : Université des Antilles. Service commun de la documentation
Permalien : http://www.manioc.org/patrimon/HASH019ae011ec18b28036fd3399
HASH019ae011ec18b28036fd3399

Éditeur(s) : HAL CCSD
Résumé : International audience
We present a novel approach towards signature recognition from spatio-temporal data. The data is obtained by recording gyroscope and accelerometer measurements from an embedded pen device. The idea of Universum learning was previously presented by Vapnik and recently popularized in machine learning community. It assumes that the decision boundary of a classifier lies close to data with high uncertainty. The quality of the final classifier strongly depends on a way how to choose the Universum data and also on the representation of original data. In our paper we use a novel approach of Universum learning to classify signature data, also we present our novel idea how to sample the Universum data. At last, we also find more effective representation of the signature data itself compared to the baseline method. These three novelties allow us to outperform previously published results by 4.89% / 5.58%.
17th Biennial Conference of the International Graphonomics Society
Pointe-à-Pitre, Guadeloupe

hal-01165925
https://hal.univ-antilles.fr/hal-01165925
https://hal.univ-antilles.fr/hal-01165925/document
https://hal.univ-antilles.fr/hal-01165925/file/IGS_2015_submission_38.pdf

Éditeur(s) : London : Saunders and Otley
Description : History of the Caribs. Culture and way of life of Antiguans in the 18th and 19th Centuries.
Siècle(s) traité(s) : 18
Droits : Domaine public
Provenance : Ville de Pointe-à-Pitre. Réseau des bibliothèques
Permalien : http://www.manioc.org/patrimon/PAP11081
PAP11081

Éditeur(s) : [S.l.] : Murray
Siècle(s) traité(s) : 15
Droits : Domaine public
Provenance : Université des Antilles. Service commun de la documentation
Permalien : http://www.manioc.org/patrimon/HASH117f75b891912290c62713
HASH117f75b891912290c62713

Éditeur(s) : Edinburgh, London
Siècle(s) traité(s) : 19
Provenance : Université Caen Normandie. Service commun de la documentation
Permalien : http://www.manioc.org/patrimon/CAE19033_2
CAE19033_2