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Your search keyword '"Sébastien Valette"' showing total 22 results
Start Over Author "Sébastien Valette" Topic 0202 electrical engineering, electronic engineering, information engineering
22 results on '"Sébastien Valette"'

1. Learning 3D medical image keypoint descriptors with the triplet loss

Author

Sébastien Valette, Nicolas Loiseau–witon, Razmig Kéchichian, Adrien Bartoli, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Imagerie Tomographique et Radiothérapie, Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Modeling & analysis for medical imaging and Diagnosis (MYRIAD), Institut Pascal (IP), 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), Valette, Sébastien, 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 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)-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 de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-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), and ANR-19-CE45-0015,TOPACS,Traitement Ouvert de données PACS(2019)

Subjects
Databases, Factual, Matching (graph theory), Computer science, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Biomedical Engineering, Health Informatics, 02 engineering and technology, Convolutional neural network, Descriptors, Synthetic data, Image (mathematics), Imaging, Three-Dimensional, Triplet loss, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, 0202 electrical engineering, electronic engineering, information engineering, Medical imaging, Humans, Radiology, Nuclear Medicine and imaging, Convolution Neural Network, business.industry, Reproducibility of Results, 020207 software engineering, Pattern recognition, General Medicine, Keypoints, Computer Graphics and Computer-Aided Design, Computer Science Applications, High memory, ComputingMethodologies_PATTERNRECOGNITION, Benchmark (computing), 020201 artificial intelligence & image processing, Surgery, Computer Vision and Pattern Recognition, Affine transformation, Artificial intelligence, Tomography, X-Ray Computed, business, Algorithms
Abstract

International audience; Purpose: We propose to learn a 3D keypoint descriptor which we use to match keypoints extracted from full-body CT scans. Our methods are inspired by 2D keypoint descriptor learning, which was shown to outperform hand-crafted descriptors. Adapting these to 3D images is challenging because of the lack of labelled training data and high memory requirements.Method: We generate semi-synthetic training data. For that, we first estimate the distribution of local affine inter-subject transformations using labelled anatomical landmarks on a small subset of the database. We then sample a large number of transformations and warp unlabelled CT scans, for which we can subsequently establish reliable keypoint correspondences using guided matching. These correspondences serve as training data for our descriptor, which we represent by a CNN and train using the triplet loss with online triplet mining.Results: We carry out experiments on a synthetic data reliability benchmark and a registration task involving 20 CT volumes with anatomical landmarks used for evaluation purposes. Our learned descriptor outperforms the 3D-SURF descriptor on both benchmarks while having a similar runtime.Conclusion: We propose a new method to generate semi-synthetic data and a new learned 3D keypoint descriptor. Experiments show improvement compared to a hand-crafted descriptor. This is promising as literature has shown that jointly learning a detector and a descriptor gives further performance boost.

Published
2021

2. Automatic Multiorgan Segmentation via Multiscale Registration and Graph Cut

Author

Michel Desvignes, Razmig Kéchichian, Sébastien Valette, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Images et Modèles, Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), GIPSA - Communication Information and Complex Systems (GIPSA-CICS), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), KECHICHIAN, Razmig, 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), and 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)

Subjects
Radiography, Abdominal, Databases, Factual, Registration, Computer science, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, spatial prior, Feature extraction, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, 02 engineering and technology, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Segmentation, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Histogram, Cut, Abdomen, 0202 electrical engineering, electronic engineering, information engineering, Image Processing, Computer-Assisted, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Humans, X-ray imaging and computed tomography, Magnetic resonance imaging (MRI), Electrical and Electronic Engineering, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, thorax, graph cut, Radiological and Ultrasound Technology, business.industry, Probabilistic logic, Pattern recognition, Atlases, Image segmentation, Magnetic Resonance Imaging, Graph, Computer Science Applications, Graph (abstract data type), Adjacency list, 020201 artificial intelligence & image processing, Radiography, Thoracic, Artificial intelligence, keypoints, business, Tomography, X-Ray Computed, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Software, Algorithms
Abstract

International audience; We propose an automatic multiorgan segmentation method for 3D radiological images of different anatomical content and modality. The approach is based on a simultaneous multilabel Graph Cut optimization of location, appearance and spatial configuration criteria of target structures. Organ location is defined by target-specific probabilistic atlases (PA) constructed from a training dataset using a fast (2+1)D SURF-based multiscale registration method involving a simple 4-parameter transformation. PAs are also used to derive target-specific organ appearance models represented as intensity histograms. The spatial configuration prior is derived from shortest-path constraints defined on the adjacency graph of structures. Thorough evaluations on Visceral project benchmarks and training dataset, as well as comparisons with the state of the art confirm that our approach is comparable to and often outperforms similar approaches in multiorgan segmentation, thus proving that the combination of multiple suboptimal but complementary information sources can yield very good performance.

Published
2018

3. Sparse Geometric Representation Through Local Shape Probing

Author

Sébastien Valette, Julie Digne, Raphaëlle Chaine, Modélisation Géométrique, Géométrie Algorithmique, Fractales (GeoMod), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), 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), Agence Nationale de la Recherche, ANR-14-CE27-0003,PAPS,Contextes locaux pour le traitement de surfaces(2014), Digne, Julie, Appel à projets générique - Contextes locaux pour le traitement de surfaces - - PAPS2014 - ANR-14-CE27-0003 - Appel à projets générique - VALID, Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), 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)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), and 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)

Subjects
Computational Geometry (cs.CG), FOS: Computer and information sciences, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, [MATH] Mathematics [math], 02 engineering and technology, [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Computer Science - Graphics, Heat kernel signature, Local shape descriptor, Active shape model, 0202 electrical engineering, electronic engineering, information engineering, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.5: Computational Geometry and Object Modeling/I.3.5.2: Curve, surface, solid, and object representations, [MATH]Mathematics [math], ComputingMethodologies_COMPUTERGRAPHICS, business.industry, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020207 software engineering, Pattern recognition, Shape similarity, Computer Graphics and Computer-Aided Design, Graphics (cs.GR), [INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG], Point distribution model, Signal Processing, Point set denoising and resampling, Computer Science - Computational Geometry, 68U05, 97R60, 020201 artificial intelligence & image processing, Topological skeleton, Computer Vision and Pattern Recognition, Artificial intelligence, business, Software, Surface reconstruction, Shape analysis (digital geometry), Curse of dimensionality
Abstract

International audience; We propose a new shape analysis approach based on the non-local analysis of local shape variations. Our method relies on a novel description of shape variations, called Local Probing Field (LPF), which describes how a local probing operator transforms a pattern onto the shape. By carefully optimizing the position and orientation of each descriptor, we are able to capture shape similarities and gather them into a geometrically relevant dictionary over which the shape decomposes sparsely. This new representation permits to handle shapes with mixed intrinsic dimensionality (e.g. shapes containing both surfaces and curves) and to encode various shape features such as boundaries. Our shape representation has several potential applications; here we demonstrate its efficiency for shape resampling and point set denoising for both synthetic and real data. Index Terms—Shape similarity-Local shape descriptor-Point set denoising and resampling.

Published
2018

4. Multi-atlas automatic positioning of anatomical landmarks

Author

Sébastien Valette, Hector Jacinto, Rémy Prost, Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Landmark, Computer science, Atlas (topology), business.industry, Multi atlas, Anatomical structures, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Iterative closest point, 020207 software engineering, 02 engineering and technology, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Signal Processing, 0202 electrical engineering, electronic engineering, information engineering, Media Technology, 020201 artificial intelligence & image processing, Computer vision, Polygon mesh, Computer Vision and Pattern Recognition, Artificial intelligence, Electrical and Electronic Engineering, business, ComputingMilieux_MISCELLANEOUS
Abstract

We propose a method for the automatic positioning of pre-defined landmarks on 3-D models of anatomical structures. We exploit a group of atlases consisting of multiple triangular meshes for which the defined landmarks have been placed by experts. We compute an initial coarse global registration of the patient mesh with an expert mesh by using a curvature-enhanced Iterative Closest Point (ICP) algorithm. Adaptive local rigid registrations refine the fit for the projection of reference landmarks onto the surface of the patient structure. An automatic selection based on a fit criterion computes a final position for each landmark. Our positioning method improves the efficiency of the positioning task, being completely unsupervised and yielding results competitive with those of the manual positioning. We provide comparisons with previous works of the literature. The automatic positioning for each target structure is completely reproducible as opposed to manual positioning, affected by intra-operator variability.

Published
2018

5. Automatic Multiorgan Segmentation Using Hierarchically Registered Probabilistic Atlases

Author

Razmig Kéchichian, Sébastien Valette, and Michel Desvignes

Subjects
Computer science, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Probabilistic logic, 020207 software engineering, Pattern recognition, 02 engineering and technology, Image (mathematics), Computer Science::Computer Vision and Pattern Recognition, Cut, 0202 electrical engineering, electronic engineering, information engineering, Graph (abstract data type), Adjacency list, 020201 artificial intelligence & image processing, Segmentation, Artificial intelligence, Cluster analysis, business, Voronoi diagram
Abstract

We propose a generic method for the automatic multiple-organ segmentation of 3D images based on a multilabel graph cut optimization approach which uses location likelihood of organs and prior information of spatial relationships between them. The latter is derived from shortest-path constraints defined on the adjacency graph of structures and the former is defined by probabilistic atlases learned from a training dataset. Organ atlases are mapped to the image by a fast (2+1)D hierarchical registration method based on SURF keypoints. Registered atlases are also used to derive organ intensity likelihoods. Prior and likelihood models are then introduced in a joint centroidal Voronoi image clustering and graph cut multiobject segmentation framework. Qualitative and quantitative evaluation has been performed on contrast-enhanced CT and MR images from the VISCERAL dataset.

Published
2017

6. Self-similarity for accurate compression of point sampled surfaces

Author

Sébastien Valette, Raphaëlle Chaine, and Julie Digne

Subjects
Surface (mathematics), Self-similarity, Property (programming), business.industry, Computer science, Point cloud, 020207 software engineering, 02 engineering and technology, Computer Graphics and Computer-Aided Design, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Point (geometry), Artificial intelligence, Noise (video), business, Representation (mathematics), Algorithm, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Most surfaces, be it from a fine-art artifact or a mechanical object, are characterized by a strong self-similarity. This property finds its source in the natural structures of objects but also in the fabrication processes: regularity of the sculpting technique, or machine tool. In this paper, we propose to exploit the self-similarity of the underlying shapes for compressing point cloud surfaces which can contain millions of points at a very high precision. Our approach locally resamples the point cloud in order to highlight the self-similarity of the shape, while remaining consistent with the original shape and the scanner precision. It then uses this self-similarity to create an ad hoc dictionary on which the local neighborhoods will be sparsely represented, thus allowing for a light-weight representation of the total surface. We demonstrate the validity of our approach on several point clouds from fine-arts and mechanical objects, as well as a urban scene. In addition, we show that our approach also achieves a filtering of noise whose magnitude is smaller than the scanner precision.

Published
2014

7. Positioning of anatomical landmarks in orthopedics by MESH registration

Author

R. Kechichian, Sébastien Valette, Hector Jacinto, Rémy Prost, Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, business.industry, Computer science, Physics::Medical Physics, Constraint (computer-aided design), ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Iterative closest point, 020207 software engineering, 02 engineering and technology, Curvature, Computer Science::Graphics, Dimension (vector space), Robustness (computer science), Computer Science::Computer Vision and Pattern Recognition, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, Scale (map), ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; We propose a system for automatic positioning of identified landmarks on anatomical structures generated from medical images. We obtain a rigid registration of 3-D shapes using the Iterative Closest Point (ICP) algorithm where a curvature constraint is added as a supplementary dimension in order to improve robustness. A dichotomic scale search and a local rigid registration allow fast local adjustment. We show the effectiveness of the proposed approach by comparing the automatic positioning of anatomical landmarks against the manual positioning by a trained operator.

Published
2014

8. Approximated Centroidal Voronoi Diagrams for Uniform Polygonal Mesh Coarsening

Author

Sébastien Valette, Jean-Marc Chassery, Laboratoire des images et des signaux (LIS), and Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Université Joseph Fourier - Grenoble 1 (UJF)

Subjects
Tessellation, Computer science, Triangulation (social science), 020207 software engineering, 02 engineering and technology, Volume mesh, Computer Science::Computational Geometry, Topology, Lloyd's algorithm, Computer Graphics and Computer-Aided Design, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Polygon, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Polygon mesh, Power diagram, Centroidal Voronoi tessellation, Cluster analysis, Voronoi diagram, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Eurographics 2004 proceedings; International audience; We present a novel clustering algorithm for polygonal meshes which approximates a Centroidal Voronoi Diagram construction. The clustering provides an efficient way to construct uniform tessellations, and therefore leads to uniform coarsening of polygonal meshes, when the output triangulation has many fewer elements than the input mesh. The mesh topology is also simplified by the clustering algorithm. Based on a mathematical framework, our algorithm is easy to implement, and has low memory requirements. We demonstrate the efficiency of the proposed scheme by processing several reference meshes having up to 1 million triangles and very high genus within a few minutes on a low-end computer.

Published
2004

9. Shortest-path constraints for 3D multiobject semiautomatic segmentation via clustering and Graph Cut

Author

Sébastien Valette, Michel Desvignes, Razmig Kéchichian, Rémy Prost, Valette, Sébastien, Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), 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)-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), GIPSA - Architecture, Géométrie, Perception, Images, Gestes (GIPSA-AGPIG), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Région Rhone Alpes (SIMED), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Scale-space segmentation, 02 engineering and technology, Sensitivity and Specificity, 030218 nuclear medicine & medical imaging, Pattern Recognition, Automated, 03 medical and health sciences, 0302 clinical medicine, Imaging, Three-Dimensional, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Artificial Intelligence, Cut, Image Interpretation, Computer-Assisted, 0202 electrical engineering, electronic engineering, information engineering, Segmentation, Cluster analysis, Mathematics, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, business.industry, Segmentation-based object categorization, Reproducibility of Results, Pattern recognition, Numerical Analysis, Computer-Assisted, Image segmentation, Image Enhancement, Computer Graphics and Computer-Aided Design, Region growing, 020201 artificial intelligence & image processing, Artificial intelligence, business, Connected-component labeling, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Software, Algorithms
Abstract

International audience; We derive shortest-path constraints from graph models of structure adjacency relations and introduce them in a joint centroidal Voronoi image clustering and Graph Cut multiobject semiautomatic segmentation framework. The vicinity prior model thus defined is a piecewise-constant model incurring multiple levels of penalization capturing the spatial configuration of structures in multiobject segmentation. Qualitative and quantitative analyses and comparison with a Potts prior-based approach and our previous contribution on synthetic, simulated, and real medical images show that the vicinity prior allows for the correct segmentation of distinct structures having identical intensity profiles and improves the precision of segmentation boundary placement while being fairly robust to clustering resolution. The clustering approach we take to simplify images prior to segmentation strikes a good balance between boundary adaptivity and cluster compactness criteria furthermore allowing to control the trade-off. Compared with a direct application of segmentation on voxels, the clustering step improves the overall runtime and memory footprint of the segmentation process up to an order of magnitude without compromising the quality of the result.

Published
2013

10. A web interface for 3D visualization and interactive segmentation of medical images

Author

Michel Desvignes, Hector Jacinto, Rémy Prost, Sébastien Valette, Razmig Kéchichian, Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), GIPSA - Architecture, Géométrie, Perception, Images, Gestes (GIPSA-AGPIG), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-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)-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), and Valette, Sébastien

Subjects
[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Scale-space segmentation, 02 engineering and technology, HTML5, 3D rendering, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, meshing, Computer graphics (images), Digital image processing, WebGL, 0202 electrical engineering, electronic engineering, information engineering, Computer vision, Segmentation, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, business.industry, segmentation, web interface, 020207 software engineering, Image segmentation, Visualization, Remote procedure call, graph-cuts, 020201 artificial intelligence & image processing, Artificial intelligence, User interface, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, clustering
Abstract

International audience; We propose a web-accessible image visualization and processing framework well-suited for medical applications. Exploiting client-side HTML5 and WebGL technologies, our proposal allows the end-user to efficiently browse and visualize volumic images in an Out-Of-Core (OOC) manner, annotate and apply server-side image processing algorithms and interactively visualize 3D medical models. Server-side implementation is driven by a file-based, simple, robust and flexible Remote Procedure Call (RPC) scheme well suited for heterogeneous applications. We demonstrate the efficiency of our approach with both an interactive medical image segmentation and a 3D rendering of segmented anatomical structures. As a secondary contribution, we improve the segmentation algorithm with the introduction of user-defined anatomical priors.

Published
2012

11. 3-D mesh sequence compression using wavelet-based multi-resolution analysis

Author

Sébastien Valette, Rémy Prost, Jae W. Cho, H. Y. Jung, Ju H. Park, Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Applied Mathematics, Numerical analysis, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Wavelet transform, 020207 software engineering, Data_CODINGANDINFORMATIONTHEORY, 02 engineering and technology, Computational Mathematics, Wavelet, Redundancy (information theory), [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Mesh generation, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Algorithm, Differential coding, ComputingMilieux_MISCELLANEOUS, Image compression, Data compression, Mathematics
Abstract

In this paper, we present two compression methods for irregular three-dimensional (3-D) mesh sequences with constant connectivity. The proposed methods mainly use an exact integer spatial wavelet analysis (SWA) technique to efficiently decorrelate the spatial coherence of each mesh frame and also to adaptively transmit mesh frames with various spatial resolutions. To reduce the temporal redundancy, the first proposed method applies multi-order differential coding (MDC) to the temporal sequences obtained from SWA. MDC determines the optimal order of the differential coder by analyzing the variance of prediction errors. Comparing with the first order differential coding (FDC) scheme, the method can improve the compression performance. The second proposed method applies temporal wavelet analysis (TWA) to the temporal sequences. In particular, this method offers spatio-temporal multi-resolution coding. Through simulations, we prove that our methods enable efficient lossy-to-lossless compression for 3-D mesh sequences in a single frame work.

Published
2010

12. Exploiting curvature to compute the medial axis with Constrained Centroidal Voronoi Diagram on discrete data

Author

Sébastien Valette, Bassem Khaddour, Nicolas Siauve, Rémy Prost, Julien Dardenne, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), 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)-École Supérieure Chimie Physique Électronique de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
[SPI.NRJ]Engineering Sciences [physics]/Electric power, 020207 software engineering, 0102 computer and information sciences, 02 engineering and technology, Computer Science::Computational Geometry, Lloyd's algorithm, Topology, Curvature, 01 natural sciences, Weighted Voronoi diagram, 010201 computation theory & mathematics, Medial axis, 0202 electrical engineering, electronic engineering, information engineering, Power diagram, mage & Video Segmentation, Centroidal Voronoi tessellation, Voronoi diagram, Clustering-based method, Distance transform, ComputingMilieux_MISCELLANEOUS, Mathematics
Abstract

In this paper, we present a novel method for medial axis approximation based on Constrained Centroidal Voronoi Diagram of discrete data (image, volume). The proposed approach is based on the shape boundary subsampling controled by a clustering approach which generates a Voronoi Diagram well suited for Medial Axis extraction. The resulting Voronoi Diagram is further filtered in order to capture the correct topology of the medial axis. The main contribution of this paper is the integration of both a curvature maps and a distance map for controlling the local variability of Voronoi cells densities. Examples of complex shape processing prove the effectiveness of the proposed approach.

Published
2009

13. Variational implicit surface meshing

Author

Rémy Prost, Sébastien Valette, Wieslaw L. Nowinski, Arnaud Gelas, Harvard Medical School [Boston] (HMS), Biomedical Imaging Lab, Agency for Science, Technology and Research, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), 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)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Valette, Sébastien, Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Mathematical optimization, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, General Engineering, Triangulation (social science), Initialization, Sampling (statistics), 020207 software engineering, 02 engineering and technology, Curvature, Surface (topology), Computer Graphics and Computer-Aided Design, Vertex (geometry), Human-Computer Interaction, 03 medical and health sciences, 0302 clinical medicine, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, 0202 electrical engineering, electronic engineering, information engineering, Polygon mesh, Relaxation (approximation), Algorithm, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, 030217 neurology & neurosurgery, Mathematics, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Proceedings of IEEE International Conference on Shape Modeling and Applications SMI 2009; International audience; In this paper, we propose a new algorithm to mesh implicit surfaces which produces meshes both with a good triangle aspect ratio as well as a good approximation quality. The number of vertices of the output mesh is defined by the end-user. For this goal, we perform a two-stage processing : an initialization step followed by an iterative optimization step. The initialization step consists in capturing the surface topology and allocating the vertex budget. The optimization algorithm is based on a variational vertices relaxation and triangulation update. In addition a gradation parameter can be defined to adapt the mesh sampling to the curvature of the implicit surface. We demonstrate the efficiency of the approach on synthetic models as well as real-world acquired data, and provide comparisons with previous approaches.

Published
2009

14. Progressive Lossless Mesh Compression Via Incremental Parametric Refinement

Author

Sébastien Valette, Raphaëlle Chaine, Rémy Prost, Valette, Sébastien, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Modélisation Géométrique, Géométrie Algorithmique, Fractales (GeoMod), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), 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)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), 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)-École Supérieure Chimie Physique Électronique de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Université Lumière - Lyon 2 (UL2)

Subjects
Mathematical optimization, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, 02 engineering and technology, T-vertices, [MATH.MATH-IT] Mathematics [math]/Information Theory [math.IT], Sampling (signal processing), [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Distortion, Compression (functional analysis), 0202 electrical engineering, electronic engineering, information engineering, Polygon mesh, Parametric statistics, Mathematics, ComputingMethodologies_COMPUTERGRAPHICS, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Lossless compression, [MATH.MATH-IT]Mathematics [math]/Information Theory [math.IT], 020207 software engineering, Computer Graphics and Computer-Aided Design, Computer Science::Graphics, [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], 020201 artificial intelligence & image processing, [INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT], Algorithm, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Data compression
Abstract

Proceedings of Symposium on Geometry Processing SGP 2009; International audience; In this paper, we propose a novel progressive lossless mesh compression algorithm based on Incremental Parametric Refinement, where the connectivity is uncontrolled in a first step, yielding visually pleasing meshes at each resolution level while saving connectivity information compared to previous approaches. The algorithm starts with a coarse version of the original mesh, which is further refined by means of a novel refinement scheme. The mesh refinement is driven by a geometric criterion, in spirit with surface reconstruction algorithms, aiming at generating uniform meshes. The vertices coordinates are also quantized and transmitted in a progressive way, following a geometric criterion, efficiently allocating the bit budget. With this assumption, the generated intermediate meshes tend to exhibit a uniform sampling. The potential discrepancy between the resulting connectivity and the original one is corrected at the end of the algorithm. We provide a proof-of-concept implementation, yielding very competitive results compared to previous works in terms of rate/distortion trade-off.

Published
2009

15. Variational tetrahedral mesh generation from discrete volume data

Author

Sébastien Valette, Noël Burais, Nicolas Siauve, Julien Dardenne, Rémy Prost, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), 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)-École Supérieure Chimie Physique Électronique de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), 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)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Valette, Sébastien, Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), 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)-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), and Ampère, Publications

Subjects
[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Geometry, 0102 computer and information sciences, 02 engineering and technology, Dihedral angle, Topology, computer.software_genre, 01 natural sciences, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Voxel, 0202 electrical engineering, electronic engineering, information engineering, 5-cell, Polygon mesh, Cluster analysis, Mathematics, ComputingMethodologies_COMPUTERGRAPHICS, [SPI.NRJ]Engineering Sciences [physics]/Electric power, 020207 software engineering, Computer Graphics and Computer-Aided Design, Finite element method, Vertex (geometry), Computer Science::Graphics, 010201 computation theory & mathematics, Tetrahedron, Computer Vision and Pattern Recognition, computer, Software, [SPI.NRJ] Engineering Sciences [physics]/Electric power
Abstract

International audience; In this paper, we propose a novel tetrahedral mesh generation algorithm, which takes volumic data (voxels) as an input. Our algorithm performs a clustering of the original voxels within a variational framework. A vertex replaces each cluster and the set of created vertices is triangulated in order to obtain a tetrahedral mesh, taking into account both the accuracy of the representation and the elements quality. The resulting meshes exhibit good elements quality with respect to minimal dihedral angle and tetrahedra form factor. Experimental results show that the generated meshes are well suited for Finite Element Simulations.

Published
2009

16. Generic remeshing of 3D triangular meshes with metric-dependent discrete Voronoi Diagrams

Author

Sébastien Valette, Jean-Marc Chassery, Rémy Prost, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), 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)-École Supérieure Chimie Physique Électronique de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), GIPSA - Géométrie, Perception, Images, Geste (GIPSA-GPIG), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Valette, Sébastien, Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), and Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)

Subjects
Mathematical optimization, Computer science, Delaunay triangulation, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Discrete geometry, 020207 software engineering, 02 engineering and technology, Topology, Computational geometry, Computer Graphics and Computer-Aided Design, Vertex (geometry), [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Mesh generation, Signal Processing, Triangle mesh, Metric (mathematics), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Polygon mesh, Computer Vision and Pattern Recognition, Voronoi diagram, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Software, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; In this paper, we propose a generic framework for 3D surface remeshing. Based on a metric-driven Discrete Voronoi Diagram construction, our output is an optimized 3D triangular mesh with a user defined vertex budget. Our approach can deal with a wide range of applications, from high quality mesh generation to shape approximation. By using appropriate metric constraints the method generates isotropic or anisotropic elements. Based on point-sampling, our algorithm combines the robustness and theoretical strength of Delaunay criteria with the efficiency of entirely discrete geometry processing . Besides the general described framework, we show experimental results using isotropic, quadric-enhanced isotropic and anisotropic metrics which prove the efficiency of our method on large meshes, for a low computational cost.

Published
2008

17. Watermarking of 3D Irregular Meshes Based on Wavelet Multiresolution Analysis

Author

Min-Su Kim, Sébastien Valette, Ho-Youl Jung, Rémy Prost, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), 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)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Yeungnam University [South Korea], Informatics & Telematics Institute [Thessaloniki, Greece], Valette, Sébastien, Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Discrete wavelet transform, Theoretical computer science, Steganography, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Computer science, Multiresolution analysis, 020207 software engineering, Watermark, 02 engineering and technology, Lossy compression, Wavelet, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Computer Science::Multimedia, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Polygon mesh, Affine transformation, Algorithm, Digital watermarking, Computer Science::Cryptography and Security
Abstract

International audience; In this paper, we propose a robust watermarking method for 3-D triangle surface meshes. Most previous methods based on the wavelet analysis can process only semi-regular meshes. Our proposal can be applied to irregular as well as regular meshes by using recently introduced irregular wavelet analysis scheme. L2-Norm of the wavelet coefficients is modified in various multi-resolution levels to embed the watermark. We also introduced a vertex and face reordering process as pre-processing in both watermark embedding and extraction for the robustness against connectivity reordering attacks. In addition, our proposal employs blind watermark detection scheme, which can extract the watermark without reference of cover mesh model. Through the simulations, we prove that our approach is robust against connectivity reordering as well as various kinds of geometrical attacks such as lossy compression and affine transform.

Published
2005

18. Wavelet-based multiresolution analysis of irregular surface meshes

Author

Sébastien Valette, P. Prost, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Valette, Sébastien, Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Computer science, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Multiresolution analysis, Information Storage and Retrieval, 02 engineering and technology, Volume mesh, T-vertices, Sensitivity and Specificity, Mathematics::Numerical Analysis, Pattern Recognition, Automated, User-Computer Interface, Wavelet, Imaging, Three-Dimensional, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Image Interpretation, Computer-Assisted, 0202 electrical engineering, electronic engineering, information engineering, Computer Graphics, Polygon mesh, Computer vision, Computer Simulation, Static mesh, Subdivision, ComputingMethodologies_COMPUTERGRAPHICS, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, business.industry, Reproducibility of Results, 020207 software engineering, Numerical Analysis, Computer-Assisted, Signal Processing, Computer-Assisted, Computational geometry, Image Enhancement, Computer Graphics and Computer-Aided Design, Computer Science::Graphics, Mesh generation, Signal Processing, Computer-Aided Design, 020201 artificial intelligence & image processing, Computer Vision and Pattern Recognition, Artificial intelligence, business, Algorithm, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Software, Algorithms
Abstract

International audience; This paper extends Lounsbery s multiresolution analysis wavelet-based theory for triangular 3D meshes, which can only be applied to regularly subdivided meshes and thus involves a remeshing of the existing 3D data. Based on a new irregular subdivision scheme, the proposed algorithm can be applied directly to irregular meshes, which can be very interesting when one wants to keep the connectivity and geometry of the processed mesh completely unchanged. This is very convenient in CAD (Computer-Assisted Design), when the mesh has attributes such as texture and color information, or when the 3D mesh is used for simulations, and where a different connectivity could lead to simulation errors. The algorithm faces an inverse problem for which a solution is proposed. For each level of resolution, the simplification is processed in order to keep the mesh as regular as possible. In addition, a geometric criterion is used to keep the geometry of the approximations as close as possible to the original mesh. Several examples on various reference meshes are shown to prove the efficiency of our proposal.

Published
2004

19. Mesh-based video objects tracking combining motion and luminance discontinuities criteria

Author

Isabelle E. Magnin, Sébastien Valette, Rémy Prost, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Boundary (topology), 02 engineering and technology, Classification of discontinuities, Tracking (particle physics), Luminance, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Motion estimation, 0202 electrical engineering, electronic engineering, information engineering, Computer vision, Electrical and Electronic Engineering, ComputingMilieux_MISCELLANEOUS, ComputingMethodologies_COMPUTERGRAPHICS, Mathematics, business.industry, 020206 networking & telecommunications, Object detection, Control and Systems Engineering, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Signal Processing, 020201 artificial intelligence & image processing, Computer Vision and Pattern Recognition, Artificial intelligence, business, Distance transform, Software, Energy (signal processing)
Abstract

A new content-based mesh design algorithm for video objects segmentation and tracking is proposed. The algorithm moves the mesh nodes along motion or luminance discontinuities in order to fit the objects boundaries. The motion inside adjacent triangular cells is estimated by competitive forward-backward matching. This approach allows the displacements of the nodes without the remeshing of occlusion regions: uncovered background nor background to be covered. The mesh is deformed under the minimization of an objective function. This function includes a motion energy, a spatial boundary energy and a temporal regularization energy. The motion energy is effective in textured regions while the boundary energy mainly operates in homogeneous one according to a boundary distance map. The temporal regularization energy keeps the objects tracking stable along the sequence due to its object-based approach. Experimental results with both synthetic and real-world sequences prove the efficiency of the proposed approach and the cooperative action of the three energy terms.

Published
2004

20. Compression of 3D Triangular Meshes with Progressive Precision

Author

Alexandre Gouaillard, Sébastien Valette, Rémy Prost, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), 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)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Valette, Sébastien, Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Floating point, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, General Engineering, 020207 software engineering, Geometry, 02 engineering and technology, Volume mesh, Data_CODINGANDINFORMATIONTHEORY, Lossy compression, Computer Graphics and Computer-Aided Design, Human-Computer Interaction, Transformation (function), Wavelet, Computer Science::Graphics, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Compression (functional analysis), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Polygon mesh, Quantization (image processing), Algorithm, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Mathematics, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; In this paper we introduce a novel approach for progressive transmission of three-dimensional (3D) triangular meshes. This algorithm is based on a new reversing approach of the irregular mesh subdivision that enables a wavelet representation of any mesh geometry. In this paper, we show how to achieve progressive compression of 3D models by transmitting more and more wavelet coef cients computed from the original mesh vertices coordinates. The connectivity of the reconstructed mesh remains the same as the original one, but its geometry is progressively re ned by means of bitplane encoding. This approach processes directly oating point coordinates which is the most common representation for 3D meshes, and does not need quantization, which is a lossy transformation. Experimental results are given and demonstrate the efficiency of our encoding scheme versus other approaches.

Published
2004

21. A Wavelet-Based Progressive Compression Scheme For Triangle Meshes : Wavemesh

Author

Rémy Prost, Sébastien Valette, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Valette, Sébastien, Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Computer science, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, 02 engineering and technology, Volume mesh, Data_CODINGANDINFORMATIONTHEORY, Lossy compression, Sensitivity and Specificity, Pattern Recognition, Automated, User-Computer Interface, Imaging, Three-Dimensional, Wavelet, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Image Interpretation, Computer-Assisted, Computer Graphics, 0202 electrical engineering, electronic engineering, information engineering, Computer Simulation, Computer vision, Polygon mesh, Image resolution, ComputingMethodologies_COMPUTERGRAPHICS, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Lossless compression, business.industry, Reproducibility of Results, Wavelet transform, Numerical Analysis, Computer-Assisted, Signal Processing, Computer-Assisted, 020207 software engineering, Data Compression, Image Enhancement, Computer Graphics and Computer-Aided Design, Signal Processing, Computer-Aided Design, 020201 artificial intelligence & image processing, Computer Vision and Pattern Recognition, Artificial intelligence, business, Algorithm, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Algorithms, Software, Data compression
Abstract

International audience; This paper proposes a new lossy to lossless progressive compression scheme for triangular meshes, based on a wavelet multiresolution theory for irregular 3D meshes. Although remeshing techniques obtain better compression ratios for geometric compression, this approach can be very effective when one wants to keep the connectivity and geometry of the processed mesh completely unchanged. The simplification is based on the solving of an inverse problem. Optimization of both the connectivity and geometry of the processed mesh improves the approximation quality and the compression ratio of the scheme at each resolution level. We show why this algorithm provides an efficient means of compression for both connectivity and geometry of 3D meshes and it is illustrated by experimental results on various sets of reference meshes, where our algorithm performs better than previously published approaches for both lossless and progressive compression.

Published
2004

22. AN EFFICIENT SUBDIVISION INVERSION FOR WAVEMESH-BASED PROGRESSIVE COMPRESSION OF 3D TRIANGLE MESHES

Author

Jarek Rossignac, Sébastien Valette, Rémy Prost, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), 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)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), School of Interactive Computing & GVU Center, Georgia Institute of Technology, Georgia Institute of Technology [Atlanta], Valette, Sébastien, Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Lossless compression, Theoretical computer science, Texture compression, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, 020207 software engineering, 02 engineering and technology, Data_CODINGANDINFORMATIONTHEORY, Lossy compression, T-vertices, Computer Science::Graphics, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Triangle mesh, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Polygon mesh, Algorithm, Image compression, Data compression, Mathematics, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; Wavemesh is a powerful scheme for 3D triangular mesh processing. In sharp contrast with other approaches using wavelets for mesh compression which apply only to meshes having subdivision connectivity, Wavemesh can simplify, approximate, and compress meshes even if they do not respect this constraint. Results clearly indicate that Wavemesh outperforms the other approaches in terms of progressive lossless compression. We propose in this paper an improvement for our scheme : higher efficiency for meshes with large subdivision connectivity sets, as shown by experimental results. Also, in some cases, the enhanced Wavemesh can even perform better than mono-resolution approaches in terms of connec-tivity compression.

Published
2003

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