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14 results on '"Favreau, Jean-Marie"'

3. A Web GIS to Generate Audio-Tactile Maps for Visually Impaired People

Author

Touya, Guillaume, Braikeh, Samuel, Campbell, Ridley, Favreau, Jean-Marie, Kalsron, Jérémy, Laboratoire sciences et technologies de l'information géographique (LaSTIG), Ecole des Ingénieurs de la Ville de Paris (EIVP)-École nationale des sciences géographiques (ENSG), Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel-Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Georg Gartner, Andrea Binn, Olesia Ignateva, and ANR-19-CE19-0005,ACTIVmap,Assistance à la Conception de carTes pour défIcients Visuels(2019)

Subjects
tactile map, visual impairment, web GIS, [INFO]Computer Science [cs], General Medicine, map generalisation
Published
2022
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5. CrossroadsDescriber – Automatic Textual Description of OpenStreetMap Intersections

Author

Kalsron, Jérémy, Favreau, Jean-Marie, Touya, Guillaume, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Laboratoire sciences et technologies de l'information géographique (LaSTIG), Ecole des Ingénieurs de la Ville de Paris (EIVP)-École nationale des sciences géographiques (ENSG), Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel-Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel, Centre de recherche nantais Architectures Urbanités (CRENAU ), Ambiances, Architectures, Urbanités (AAU), Ministère de la Culture et de la Communication (MCC)-Centre National de la Recherche Scientifique (CNRS)-École nationale supérieure d'architecture de Grenoble (ENSAG ), Université Grenoble Alpes (UGA)-Université Grenoble Alpes (UGA)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-NANTES UNIVERSITÉ - École nationale supérieure d'architecture de Nantes (Nantes Univ - ENSA Nantes), Nantes Université (Nantes Univ)-Ministère de la Culture et de la Communication (MCC)-Centre National de la Recherche Scientifique (CNRS)-École nationale supérieure d'architecture de Grenoble (ENSAG ), Nantes Université (Nantes Univ), and ANR-19-CE19-0005,ACTIVmap,Assistance à la Conception de carTes pour défIcients Visuels(2019)

Subjects
[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], General Earth and Planetary Sciences, General Environmental Science
Abstract

Crossing an intersection is a challenge for visually impaired people. While tactile maps can be a medium for appropriating this complex space, they benefit from being complemented by audio information. In this paper we propose a data model to describe an intersection, the paths that allow to cross it, and their accessibility attributes. We also present methods to generate this model automatically from OpenStreetMap, by inferring missing data through graph analysis techniques. Finally, we present an implementation, the evaluation of which confirms the ability of the model to generate a compliant description for intersections with enough data.

Published
2022
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6. Cortical surface mapping using topology correction, partial flattening and 3D shape context-based non-rigid registration for use in quantifying atrophy in Alzheimer's disease

Author

Acosta, Oscar, Fripp, Jurgen, Doré, Vincent, Bourgeat, Pierrick, Favreau, Jean-Marie, Chételat, Gaël, Rueda, Andrea, Villemagne, Victor L., Szoeke, Cassandra, Ames, David, Ellis, Kathryn A., Martins, Ralph N., Masters, Colin L., Rowe, Christopher C., Bonner, Erik, Gris, Florence, Xiao, Di, Raniga, Parnesh, Barra, Vincent, and Salvado, Olivier

Published
2012
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8. Schematizing Crossroads from Abstract Textual Descriptions

Author

Favreau, Jean-Marie, Touya, Guillaume, Kalsron, Jérémy, Touya, Guillaume, Assistance à la Conception de carTes pour défIcients Visuels - - ACTIVmap2019 - ANR-19-CE19-0005 - AAPG2019 - VALID, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Laboratoire sciences et technologies de l'information géographique (LaSTIG), Ecole des Ingénieurs de la Ville de Paris (EIVP)-École nationale des sciences géographiques (ENSG), Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel-Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel, Centre de recherche nantais Architectures Urbanités (CRENAU ), Ambiances, Architectures, Urbanités (AAU), Ministère de la Culture et de la Communication (MCC)-Centre National de la Recherche Scientifique (CNRS)-École nationale supérieure d'architecture de Grenoble (ENSAG ), Université Grenoble Alpes (UGA)-Université Grenoble Alpes (UGA)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-NANTES UNIVERSITÉ - École nationale supérieure d'architecture de Nantes (Nantes Univ - ENSA Nantes), Nantes Université (Nantes Univ)-Ministère de la Culture et de la Communication (MCC)-Centre National de la Recherche Scientifique (CNRS)-École nationale supérieure d'architecture de Grenoble (ENSAG ), Nantes Université (Nantes Univ), University of Bonn, Germany, and ANR-19-CE19-0005,ACTIVmap,Assistance à la Conception de carTes pour défIcients Visuels(2019)

Subjects
Computational cartography, Cartography, Cartographie -- informatique, [INFO]Computer Science [cs], [INFO] Computer Science [cs], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2022

9. 3D Geometric salient patterns analysis on 3D meshes

Author

Othmani, Alice, Torkhani, Fakhri, Favreau, Jean-Marie, Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), and Favreau, Jean-Marie

Subjects
FOS: Computer and information sciences, Computer Science - Graphics, [INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG], Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], Graphics (cs.GR), ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Pattern analysis is a wide domain that has wide applicability in many fields. In fact, texture analysis is one of those fields, since the texture is defined as a set of repetitive or quasi-repetitive patterns. Despite its importance in analyzing 3D meshes, geometric texture analysis is less studied by geometry processing community. This paper presents a new efficient approach for geometric texture analysis on 3D triangular meshes. The proposed method is a scale-aware approach that takes as input a 3D mesh and a user-scale. It provides, as a result, a similarity-based clustering of texels in meaningful classes. Experimental results of the proposed algorithm are presented for both real-world and synthetic meshes within various textures. Furthermore, the efficiency of the proposed approach was experimentally demonstrated under mesh simplification and noise addition on the mesh surface. In this paper, we present a practical application for semantic annotation of 3D geometric salient texels.

Published
2020

10. Technical Report : 3D mesh Segmentation Application to glasses

Author

Bernay-Angeletti, Coralie, Favreau, Jean-Marie, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), FEDER 2014-2020 Auvergne-Rhône-Alpes, LIMOS (UMR CNRS 6158), université Clermont Auvergne, France, and Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]
Abstract

Object segmentation in meaningfull parts is an important research topic as these have become a part of many mesh and object manipulation algorithms in computer graphics, geometric modelling and computer aided design. In particular, tasks that were before realized by experts are more and more assumed by people without particular formation in geometric or computer graphic problems. So there is a need to have some ergonomic tools that have expert know-how while user keep control on specific constraints to its particular application. Here, we present how for segmentation purpose we model expert know-how and two algorithms that can be used to make segmentation task. One is generic and the other is specialized for glasses segmentations.

Published
2017

12. Fine Detection of Human Motion During Activities of Daily Living as a Clinical Indicator for the Detection and Early Treatment of Chronic Diseases: The E-Mob Project.

Author

Thivel, David, Corteval, Alice, Favreau, Jean-Marie, Bergeret, Emmanuel, Samalin, Ludovic, Costes, Frédéric, Toumani, Farouk, Dualé, Christian, Pereira, Bruno, Eschalier, Alain, Fearnbach, Nicole, Duclos, Martine, and Tournadre, Anne

Abstract

Methods to measure physical activity and sedentary behaviors typically quantify the amount of time devoted to these activities. Among patients with chronic diseases, these methods can provide interesting behavioral information, but generally do not capture detailed body motion and fine movement behaviors. Fine detection of motion may provide additional information about functional decline that is of clinical interest in chronic diseases. This perspective paper highlights the need for more developed and sophisticated tools to better identify and track the decomposition, structuration, and sequencing of the daily movements of humans. The primary goal is to provide a reliable and useful clinical diagnostic and predictive indicator of the stage and evolution of chronic diseases, in order to prevent related comorbidities and complications among patients. [ABSTRACT FROM AUTHOR]

Published
2022
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13. Automatic derivation of on-demand tactile maps for visually impaired people: first experiments and research agenda.

Author

Touya, Guillaume, Christophe, Sidonie, Favreau, Jean-Marie, and Ben Rhaiem, Amine

Subjects
*TACTILE maps, *PEOPLE with visual disabilities, *THREE-dimensional printing
Abstract

Tactile maps are essential tools for visually impaired people to comprehend space and to support the simple pedestrian trips made difficult by their disability. Tactile maps are created manually and printed by specialists, and it takes a large amount of time to create a new one, which prevents using them on demand for everyday use. As a consequence, researchers and cartographers try to automate this creation process, but the existing automated derivation processes do not include generalization or advanced stylization steps, which limits their effectiveness. This paper reports first experiments to include such complex automated cartography processes to provide on-demand tactile maps for visually impaired people. These first experiments were more intended to raise real research issues than solve them, and the paper discusses these issues in a research agenda to achieve automatically derived tactile maps. [ABSTRACT FROM AUTHOR]

Published
2019
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14. Multi-layer Ontologies for Integrated 3D Shape Segmentation and Annotation

Author

Fakhri Torkhani, Thomas Dietenbeck, Marco Attene, Jean-Marie Favreau, Ahlem Othmani, 2 - Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Image Science for Interventional Techniques ( ISIT ), Université d'Auvergne - Clermont-Ferrand I ( UdA ) -Clermont Université-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), IMATI, Istituto di Matematica Applicata e Tecnologie Informatiche ( IMATI-CNR ), Consiglio Nazionale delle Ricerche [Roma] ( CNR ) -Consiglio Nazionale delle Ricerche [Roma] ( CNR ), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes ( LIMOS ), Sigma CLERMONT ( Sigma CLERMONT ) -Université Clermont Auvergne ( UCA ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Image Science for Interventional Techniques (ISIT), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Centre National de la Recherche Scientifique (CNRS), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Istituto di Matematica Applicata e Tecnologie Informatiche (IMATI-CNR), Consiglio Nazionale delle Ricerche [Roma] (CNR)-Consiglio Nazionale delle Ricerche [Roma] (CNR), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Ecole Nationale Supérieure des Mines de St Etienne-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Favreau, Jean-Marie, Laboratoire d'Imagerie Biomédicale [Paris] (LIB), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR)-National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), and Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)

Subjects
Computer science, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020207 software engineering, Image processing, 02 engineering and technology, Geometry processing, Ontology (information science), computer.software_genre, [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Expert system, Annotation, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG], N/A, 0202 electrical engineering, electronic engineering, information engineering, [ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG], Preprocessor, Domain knowledge, 020201 artificial intelligence & image processing, Segmentation, Data mining, computer
Abstract

Mesh segmentation and semantic annotation are used as preprocessing steps formany applications, including shape retrieval, mesh abstraction, and adaptive simplification. In current practice, these two steps are done sequentially: a purely geometrical analysis is employed to extract the relevant parts, and then these parts are annotated. We introduce an original framework where annotation and segmentation are performed simultaneously, so that each of the two steps can take advantage of the other. Inspired by existing methods used in image processing, we employ an expert's knowledge of the context to drive the process while minimizing the use of geometric analysis. For each specific context a multi-layer ontology can be designed on top of a basic knowledge layer which conceptualizes 3D object features from the point of view of their geometry, topology, and possible attributes. Each feature is associated with an elementary algorithm for its detection. An expert can define the upper layers of the ontology to conceptualize a specific domain without the need to reconsider the elementary algorithms. This approach has a twofold advantage: on one hand it allows Mesh segmentation and semantic annotation are used as preprocessing steps formany applications, including shape retrieval, mesh abstraction, and adaptive simplification. In current practice, these two steps are done sequentially: a purely geometrical analysis is employed to extract the relevant parts, and then these parts are annotated. We introduce an original framework where annotation and segmentation are performed simultaneously, so that each of the two steps can take advantage of the other. Inspired by existing methods used in image processing, we employ an expert's knowledge of the context to drive the process while minimizing the use of geometric analysis. For each specific context a multi-layer ontology can be designed on top of a basic knowledge layer which conceptualizes 3D object features from the point of view of their geometry, topology, and possible attributes. Each feature is associated with an elementary algorithm for its detection. An expert can define the upper layers of the ontology to conceptualize a specific domain without the need to reconsider the elementary algorithms. This approach has a twofold advantage: on one hand it allows Mesh segmentation and semantic annotation are used as preprocessing steps formany applications, including shape retrieval, mesh abstraction, and adaptive simplification. In current practice, these two steps are done sequentially: a purely geometrical analysis is employed to extract the relevant parts, and then these parts are annotated. We introduce an original framework where annotation and segmentation are performed simultaneously, so that each of the two steps can take advantage of the other. Inspired by existing methods used in image processing, we employ an expert's knowledge of the context to drive the process while minimizing the use of geometric analysis. For each specific context a multi-layer ontology can be designed on top of a basic knowledge layer which conceptualizes 3D object features from the point of view of their geometry, topology, and possible attributes. Each feature is associated with an elementary algorithm for its detection. An expert can define the upper layers of the ontology to conceptualize a specific domain without the need to reconsider the elementary algorithms. This approach has a twofold advantage: on one hand it allows to leverage domain knowledge from experts even if they have limited or no skills in geometry processing and computer programming; on the other hand, it provides a solid ground to be easily extended in different contexts with a limited effort.

Published
2016
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