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Your search keyword '"Tougne, L."' showing total 22 results
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22 results on '"Tougne, L."'

2. A 3D Tracker for Ground-Moving Objects

Author

Rogez, M., Robinault, L., Tougne, L., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Bebis, George, editor, Boyle, Richard, editor, Parvin, Bahram, editor, Koracin, Darko, editor, McMahan, Ryan, editor, Jerald, Jason, editor, Zhang, Hui, editor, Drucker, Steven M., editor, Kambhamettu, Chandra, editor, El Choubassi, Maha, editor, Deng, Zhigang, editor, and Carlson, Mark, editor

Published
2014
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4. Video-monitoring of wood flux: recent advances and next steps

Author

Hervé Piégay, Hossein Ghaffarian Roohparvar, Pierre Lemaire, Zhang, Z., Boivin, M., Anne Senter, Aurélie Antonio, Thomas Buffin-Bélanger, Diego Lopez, Bruce Macvicar, Kristell Michel, Mignot, E., Gregory Pasternack, Nicolas Riviere, Tougne, L., Lise Vaudor, Environnement, Ville, Société (EVS), École normale supérieure de Lyon (ENS de Lyon)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), 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)-Université Jean Monnet - Saint-Étienne (UJM)-École Nationale des Travaux Publics de l'État (ENTPE)-École nationale supérieure d'architecture de Lyon (ENSAL)-Centre National de la Recherche Scientifique (CNRS), Department of Land, Air and Water Resources, University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), Université du Québec à Rimouski (UQAR), Laboratoire de Mecanique des Fluides et d'Acoustique (LMFA), 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 de Lyon, Extraction de Caractéristiques et Identification (imagine), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), 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 Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Environnement Ville Société (EVS), École normale supérieure - Lyon (ENS Lyon)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet [Saint-Étienne] (UJM)-École Nationale des Travaux Publics de l'État (ENTPE)-École nationale supérieure d'architecture de Lyon (ENSAL)-Centre National de la Recherche Scientifique (CNRS), University of California-University of California, 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
[SDE.ES]Environmental Sciences/Environmental and Society, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019

8. Segmenting Simplified Surface Skeletons

Author

Reniers, D., Telea, A.C., Coeurjolly, D., Sivignon, I., Tougne, L., Dupont, F., Algorithms, Geometry and Applications, and Scientific Visualization and Computer Graphics

Subjects
Surface (mathematics), Geodesic, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Boundary (topology), Skeleton (category theory), computer.software_genre, Measure (mathematics), Medial axis, Voxel, Computer vision, Noise (video), Artificial intelligence, business, Algorithm, computer, ComputingMethodologies_COMPUTERGRAPHICS, Mathematics
Abstract

A novel method for segmenting simplified skeletons of 3D shapes is presented. The so-called simplified Y-network is computed, defining boundaries between 2D sheets of the simplified 3D skeleton, which we take as our skeleton segments. We compute the simplified Y-network using a robust importance measure which has been proved useful for simplifying complex 3D skeleton manifolds. We present a voxel-based algorithm and show results on complex real-world objects, including ones containing large amounts of boundary noise.

Published
2008

17. Late Information Fusion for Multi-modality Plant Species Identification

Author

Cerutti, G., Tougne, L., Sacca, C., Joliveau, T., Pierre-Olivier MAZAGOL, Coquin, D., Vacavant, A., Geometry Processing and Constrained Optimization (M2DisCo), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-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), Environnement Ville Société (EVS), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-École nationale supérieure d'architecture de Lyon (ENSAL)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École Nationale des Travaux Publics de l'État (ENTPE)-Université Jean Monnet [Saint-Étienne] (UJM)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université Lumière - Lyon 2 (UL2)-École normale supérieure - Lyon (ENS Lyon), Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Image Science for Interventional Techniques (ISIT), Université d'Auvergne - Clermont-Ferrand I (UdA)-Centre National de la Recherche Scientifique (CNRS)-Clermont Université, 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), Environnement, Ville, Société (EVS), École normale supérieure de Lyon (ENS de Lyon)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), 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)-Université Jean Monnet - Saint-Étienne (UJM)-École Nationale des Travaux Publics de l'État (ENTPE)-École nationale supérieure d'architecture de Lyon (ENSAL)-Centre National de la Recherche Scientifique (CNRS), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Centre National de la Recherche Scientifique (CNRS), and Cerutti, Guillaume

Subjects
[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], biogeographical information, confidence fusion, plant identification
Abstract

International audience; This article presents the participation of the ReVeS project to the ImageCLEF 2013 Plant Identification challenge. Our primary target being tree leaves, some extra effort had to be done this year to process images containing other plant organs. The proposed method tries to benefit from the presence of multiple sources of information for a same individual through the introduction of a late fusion system based on the decisions of classifiers for the different modalities. It also presents a way to incorporate the geographical information in the determination of the species by estimating their plausibility at the considered location. While maintaining its performance on leaf images (ranking 3rd on natural images and 4th on plain backgrounds) our team performed honorably on the brand new modalities with a 6th position.

19. Registering Unmanned Aerial Vehicle Videos in the Long Term.

Author

Lemaire P, Crispim-Junior CF, Robinault L, and Tougne L

Abstract

Unmanned aerial vehicles (UAVs) have become a very popular way of acquiring video within contexts such as remote data acquisition or surveillance. Unfortunately, their viewpoint is often unstable, which tends to impact the automatic processing of their video flux negatively. To counteract the effects of an inconsistent viewpoint, two video processing strategies are classically adopted, namely registration and stabilization, which tend to be affected by distinct issues, namely jitter and drifting. Following our prior work, we suggest that the motion estimators used in both situations can be modeled to take into account their inherent errors. By acknowledging that drifting and jittery errors are of a different nature, we propose a combination that is able to limit their influence and build a hybrid solution for jitter-free video registration. In this work, however, our modeling was restricted to 2D-rigid transforms, which are rather limited in the case of airborne videos. In the present paper, we extend and refine the theoretical ground of our previous work. This addition allows us to show how to practically adapt our previous work to perspective transforms, which our study shows to be much more accurate for this problem. A lightweight implementation enables us to automatically register stationary UAV videos in real time. Our evaluation includes traffic surveillance recordings of up to 2 h and shows the potential of the proposed approach when paired with background subtraction tasks.

Published
2021
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20. On the value of CTIS imagery for neural-network-based classification: a simulation perspective.

Author

Douarre C, Crispim-Junior CF, Gelibert A, Tougne L, and Rousseau D

Abstract

The computed tomography imaging spectrometer (CTIS) is a snapshot hyperspectral imaging system. Its output is a 2D image of multiplexed spatiospectral projections of the hyperspectral cube of the scene. Traditionally, the 3D cube is reconstructed from this image before further analysis. In this paper, we show that it is possible to learn information directly from the CTIS raw output, by training a neural network to perform binary classification on such images. The use case we study is an agricultural one, as snapshot imagery is used substantially in this field: the detection of apple scab lesions on leaves. To train the network appropriately and to study several degrees of scab infection, we simulated CTIS images of scabbed leaves. This was made possible with a novel CTIS simulator, where special care was taken to preserve realistic pixel intensities compared to true images. To the best of our knowledge, this is the first application of compressed learning on a simulated CTIS system.

Published
2020
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21. Automatic Land Cover Reconstruction From Historical Aerial Images: An Evaluation of Features Extraction and Classification Algorithms.

Author

Ratajczak R, Crispim-Junior CF, Faure E, Fervers B, and Tougne L

Abstract

The land cover reconstruction from monochromatic historical aerial images is a challenging task that has recently attracted an increasing interest from the scientific community with the proliferation of large-scale epidemiological studies involving retrospective analysis of spatial patterns. However, the efforts made by the computer vision community in remote-sensing applications are mostly focused on prospective approaches through the analysis of high-resolution multi-spectral data acquired by the advanced spatial programs. Hence, four contributions are proposed in this paper. They aim at providing a comparison basis for the future development of computer vision algorithms applied to the automation of the land cover reconstruction from monochromatic historical aerial images. First, a new multi-scale multi-date dataset composed of 4.9 million non-overlapping annotated patches of the France territory between 1970 and 1990 has been created with the help of geography experts. This dataset has been named HistAerial. Second, an extensive comparison study of the state-of-the-art texture features extraction and classification algorithms, including deep convolutional neural networks (DCNNs), has been performed. It is presented in the form of an evaluation. Third, a novel low-dimensional local texture filter named rotated-corner local binary pattern (R-CRLBP) is presented as a simplification of the binary gradient contours filter through the use of an orthogonal combination representation. Finally, a novel combination of low-dimensional texture descriptors, including the R-CRLBP filter, is introduced as a light combination of local binary patterns (LCoLBPs). The LCoLBP filter achieved state-of-the-art results on the HistAerial dataset while conserving a relatively low-dimensional feature vector space compared with the DCNN approaches (17 times shorter).

Published
2019
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22. Tree leaves extraction in natural images: comparative study of preprocessing tools and segmentation methods.

Author

Grand-Brochier M, Vacavant A, Cerutti G, Kurtz C, Weber J, and Tougne L

Subjects
Environmental Monitoring methods, Image Enhancement methods, Reproducibility of Results, Sensitivity and Specificity, Algorithms, Image Interpretation, Computer-Assisted methods, Pattern Recognition, Automated methods, Photography methods, Plant Leaves anatomy & histology, Trees anatomy & histology
Abstract

In this paper, we propose a comparative study of various segmentation methods applied to the extraction of tree leaves from natural images. This study follows the design of a mobile application, developed by Cerutti et al. (published in ReVeS Participation--Tree Species Classification Using Random Forests and Botanical Features. CLEF 2012), to highlight the impact of the choices made for segmentation aspects. All the tests are based on a database of 232 images of tree leaves depicted on natural background from smartphones acquisitions. We also propose to study the improvements, in terms of performance, using preprocessing tools, such as the interaction between the user and the application through an input stroke, as well as the use of color distance maps. The results presented in this paper shows that the method developed by Cerutti et al. (denoted Guided Active Contour), obtains the best score for almost all observation criteria. Finally, we detail our online benchmark composed of 14 unsupervised methods and 6 supervised ones.

Published
2015
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