|
Publications of Florent Lafarge
Result of the query in the list of publications :
8 Articles |
1 - A Marked Point Process for Modeling Lidar Waveforms. C. Mallet and F. Lafarge and M. Roux and U. Soergel and F. Bretar and C. Heipke. IEEE Trans. Image Processing, 19(12): pages 3204-3221, December 2010. Keywords : Clustering algorithms, Image color analysis, Image edge detection, Image segmentation, Monte Carlo Sampling, Object-based stochastic model.
@ARTICLE{mallet_tip2010,
|
author |
= |
{Mallet, C. and Lafarge, F. and Roux, M. and Soergel, U. and Bretar, F. and Heipke, C.}, |
title |
= |
{A Marked Point Process for Modeling Lidar Waveforms}, |
year |
= |
{2010}, |
month |
= |
{December}, |
journal |
= |
{IEEE Trans. Image Processing}, |
volume |
= |
{19}, |
number |
= |
{12}, |
pages |
= |
{3204-3221}, |
url |
= |
{http://dx.doi.org/10.1109/TIP.2010.2052825}, |
keyword |
= |
{Clustering algorithms, Image color analysis, Image edge detection, Image segmentation, Monte Carlo Sampling, Object-based stochastic model} |
} |
Abstract :
Lidar waveforms are 1D signals representing a train of echoes caused by reflections at different targets. Modeling these echoes with the appropriate parametric function is useful to retrieve information about the physical characteristics of the targets. This paper presents a new probabilistic model based on a marked point process which reconstructs the echoes from recorded discrete waveforms as a sequence of parametric curves. Such an approach allows to fit each mode of a waveform with the most suitable function and to deal with both, symmetric and asymmetric, echoes. The model takes into account a data term, which measures the coherence between the models and the waveforms, and a regularization term, which introduces prior knowledge on the reconstructed signal. The exploration of the associated configuration space is performed by a Reversible Jump Markov Chain Monte Carlo sampler coupled with simulated annealing. Experiments with different kinds of lidar signals, especially from urban scenes, show the high potential of the proposed approach. To further demonstrate the advantages of the suggested method, actual laser scans are classified and the results are reported. |
|
2 - Geometric Feature Extraction by a Multi-Marked Point Process . F. Lafarge and G. Gimel'farb and X. Descombes. IEEE Trans. Pattern Analysis and Machine Intelligence, 32(9): pages 1597-1609, September 2010. Keywords : Shape extraction, Spatial point process, Stochastic geometry, fast optimization, Texture, remote sensing.
@ARTICLE{pami09b_lafarge,
|
author |
= |
{Lafarge, F. and Gimel'farb, G. and Descombes, X.}, |
title |
= |
{Geometric Feature Extraction by a Multi-Marked Point Process }, |
year |
= |
{2010}, |
month |
= |
{September}, |
journal |
= |
{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
volume |
= |
{32}, |
number |
= |
{9}, |
pages |
= |
{1597-1609}, |
url |
= |
{http://dx.doi.org/10.1109/TPAMI.2009.152}, |
keyword |
= |
{Shape extraction, Spatial point process, Stochastic geometry, fast optimization, Texture, remote sensing} |
} |
Abstract :
This paper presents a new stochastic marked point process for describing images in terms of a finite library of geometric objects. Image analysis based on conventional marked point processes has already produced convincing results but at the expense of parameter tuning, computing time, and model specificity. Our more general multimarked point process has simpler parametric setting, yields notably shorter computing times, and can be applied to a variety of applications. Both linear and areal primitives extracted from a library of geometric objects are matched to a given image using a probabilistic Gibbs model, and a Jump-Diffusion process is performed to search for the optimal object configuration. Experiments with remotely sensed images and natural textures show that the proposed approach has good potential. We conclude with a discussion about the insertion of more complex object interactions in the model by studying the compromise between model complexity and efficiency. |
|
3 - Insertion of 3D-primitives in mesh-based representations: Towards compact models preserving the details. F. Lafarge and R. Keriven and M. Brédif. IEEE Trans. Image Processing, 19(7): pages 1683-1694, July 2010. Keywords : 3-D reconstruction, Graph-cut , Shape extraction, urban scenes.
@ARTICLE{lafarge_tip2010,
|
author |
= |
{Lafarge, F. and Keriven, R. and Brédif, M.}, |
title |
= |
{Insertion of 3D-primitives in mesh-based representations: Towards compact models preserving the details}, |
year |
= |
{2010}, |
month |
= |
{July}, |
journal |
= |
{IEEE Trans. Image Processing}, |
volume |
= |
{19}, |
number |
= |
{7}, |
pages |
= |
{1683-1694}, |
url |
= |
{http://dx.doi.org/10.1109/TIP.2010.2045695}, |
keyword |
= |
{3-D reconstruction, Graph-cut , Shape extraction, urban scenes} |
} |
Abstract :
We propose an original hybrid modeling process of urban scenes that represents 3-D models as a combination of mesh-based surfaces and geometric 3-D-primitives. Meshes describe details such as ornaments and statues, whereas 3-D-primitives code for regular shapes such as walls and columns. Starting from an 3-D-surface obtained by multiview stereo techniques, these primitives are inserted into the surface after being detected. This strategy allows the introduction of semantic knowledge, the simplification of the modeling, and even correction of errors generated by the acquisition process. We design a hierarchical approach exploring different scales of an observed scene. Each level consists first in segmenting the surface using a multilabel energy model optimized by -expansion and then in fitting 3-D-primitives such as planes, cylinders or tori on the obtained partition where relevant. Experiments on real meshes, depth maps and synthetic surfaces show good potential for the proposed approach. |
|
4 - Structural approach for building reconstruction from a single DSM. F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. IEEE Trans. Pattern Analysis and Machine Intelligence, 32(1): pages 135-147, January 2010.
@ARTICLE{lafarge_pami09,
|
author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
title |
= |
{Structural approach for building reconstruction from a single DSM}, |
year |
= |
{2010}, |
month |
= |
{January}, |
journal |
= |
{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
volume |
= |
{32}, |
number |
= |
{1}, |
pages |
= |
{135-147}, |
url |
= |
{http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.281}, |
keyword |
= |
{} |
} |
Abstract :
We present a new approach for building reconstruction from a single Digital Surface Model (DSM). It treats buildings as an assemblage of simple urban structures extracted from a library of 3D parametric blocks (like a LEGO set). First, the 2D-supports of the urban structures are extracted either interactively or automatically. Then, 3D-blocks are placed on the 2D-supports using a Gibbs model which controls both the block assemblage and the fitting to data. A Bayesian decision finds the optimal configuration of 3D--blocks using a Markov Chain Monte Carlo sampler associated with original proposition kernels. This method has been validated on multiple data set in a wide-resolution interval such as 0.7 m satellite and 0.1 m aerial DSMs, and provides 3D representations on complex buildings and dense urban areas with various levels of detail. |
|
5 - Automatic Building Extraction from DEMs using an Object Approach and Application to the 3D-city Modeling. F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. Journal of Photogrammetry and Remote Sensing, 63(3): pages 365-381, May 2008. Keywords : Building extraction, 3D reconstruction, Digital Elevation Model, Stochastic geometry.
@ARTICLE{lafarge_jprs08,
|
author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
title |
= |
{Automatic Building Extraction from DEMs using an Object Approach and Application to the 3D-city Modeling}, |
year |
= |
{2008}, |
month |
= |
{May}, |
journal |
= |
{Journal of Photogrammetry and Remote Sensing}, |
volume |
= |
{63}, |
number |
= |
{3}, |
pages |
= |
{365-381}, |
pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2008_lafarge_jprs08.pdf}, |
keyword |
= |
{Building extraction, 3D reconstruction, Digital Elevation Model, Stochastic geometry} |
} |
Abstract :
In this paper, we present an automatic building extraction method from Digital Elevation Models based on an object approach.
First, a rough approximation of the building footprints is realized by a method based on marked point processes: the building
footprints are modeled by rectangle layouts. Then, these rectangular footprints are regularized by improving the connection
between the neighboring rectangles and detecting the roof height discontinuities. The obtained building footprints are structured
footprints: each element represents a specific part of an urban structure. Results are finally applied to a 3D-city modeling process. |
|
6 - Détection de feux de forêt par analyse statistique d'évènements rares à partir d'images infrarouges thermiques. F. Lafarge and X. Descombes and J. Zerubia and S. Mathieu. Traitement du Signal, 24(1), 2007. Note : copyright Traitement du Signal Keywords : Gaussian Field, Rare event, DT-caracteristic, Intensity peak.
@ARTICLE{lafarge_ts06,
|
author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Mathieu, S.}, |
title |
= |
{Détection de feux de forêt par analyse statistique d'évènements rares à partir d'images infrarouges thermiques}, |
year |
= |
{2007}, |
journal |
= |
{Traitement du Signal}, |
volume |
= |
{24}, |
number |
= |
{1}, |
note |
= |
{copyright Traitement du Signal}, |
pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_lafarge_ts06.pdf}, |
keyword |
= |
{Gaussian Field, Rare event, DT-caracteristic, Intensity peak} |
} |
|
7 - Automatic building 3D reconstruction from DEMs. F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. Revue Française de Photogrammétrie et de Télédétection (SFPT), 184: pages 48--53, 2006. Keywords : 3D-reconstruction, Digital Elevation Model, Building extraction, dense urban areas.
@ARTICLE{lafarge_sfpt06,
|
author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
title |
= |
{Automatic building 3D reconstruction from DEMs}, |
year |
= |
{2006}, |
journal |
= |
{Revue Française de Photogrammétrie et de Télédétection (SFPT)}, |
volume |
= |
{184}, |
pages |
= |
{48--53}, |
url |
= |
{http://isprs.free.fr/documents/Papers/T07-32.pdf}, |
keyword |
= |
{3D-reconstruction, Digital Elevation Model, Building extraction, dense urban areas} |
} |
Abstract :
This paper is about an example of PLEIADES applications, the 3D building reconstruction. The future PLEIADES satellites are
especially well adapted to deal with 3D building reconstruction through the sub-metric resolution of images and its stereoscopic characteristics. We propose a fully automatic 3D-city model of dense urban areas using a parametric approach. First, a Digital Elevation
Model (DEM) is generated using an algorithm based on a maximum-flow formulation using three views. Then, building footprints are extracted from the DEM through an automatic method based on marked point processes : they are represented by an association of rectangles that we regularize by improving the connection of the neighboring rectangles and the facade discontinuity detection. Finally, a 3D-reconstruction method based on a skeleton process which allows to model the rooftops is proposed from the DEM and the building footprints. The different building heights constitute parameters which are estimated and then regularized by the ”K-means” algorithm including an entropy term. |
|
8 - Modèle Paramétrique pour la Reconstruction Automatique en 3D de Zones Urbaines Denses à partir d'Images Satellitaires Haute Résolution. F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. Revue Française de Photogrammétrie et de Télédétection (SFPT), 180: pages 4--12, 2005. Keywords : 3D reconstruction, Urban areas, Bayesian approach, MCMC, Satellite images. Copyright : SFPT
@ARTICLE{lafarge_sfpt05,
|
author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
title |
= |
{Modèle Paramétrique pour la Reconstruction Automatique en 3D de Zones Urbaines Denses à partir d'Images Satellitaires Haute Résolution}, |
year |
= |
{2005}, |
journal |
= |
{Revue Française de Photogrammétrie et de Télédétection (SFPT)}, |
volume |
= |
{180}, |
pages |
= |
{4--12}, |
pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2005_lafarge_sfpt05.pdf}, |
keyword |
= |
{3D reconstruction, Urban areas, Bayesian approach, MCMC, Satellite images} |
} |
|
top of the page
PhD Thesis and Habilitation |
1 - Modèles stochastiques pour la reconstruction tridimensionnelle d'environnements urbains. F. Lafarge. PhD Thesis, Ecole des Mines de Paris, October 2007. Keywords : 3D reconstruction, Urban areas, Satellite images, Structural approach, Simulated Annealing, MCMC.
@PHDTHESIS{lafarge_phd07,
|
author |
= |
{Lafarge, F.}, |
title |
= |
{Modèles stochastiques pour la reconstruction tridimensionnelle d'environnements urbains}, |
year |
= |
{2007}, |
month |
= |
{October}, |
school |
= |
{Ecole des Mines de Paris}, |
url |
= |
{http://tel.archives-ouvertes.fr/tel-00179695/en/}, |
keyword |
= |
{3D reconstruction, Urban areas, Satellite images, Structural approach, Simulated Annealing, MCMC} |
} |
Résumé :
Cette thèse aborde le problème de la reconstruction tridimensionnelle de zones urbaines à partir d'images satellitaires très haute résolution. Le contenu informatif de ce type de données est insuffisant pour permettre une utilisation efficace des nombreux algorithmes développés pour des données aériennes. Dans ce contexte, l'introduction de connaissances a priori fortes sur les zones urbaines est nécessaire. Les outils stochastiques sont particulièrement bien adaptés pour traiter cette problématique.
Nous proposons une approche structurelle pour aborder ce sujet. Cela consiste à modéliser un bâtiment comme un assemblage de modules urbains élémentaires extraits d'une bibliothèque de modèles 3D paramétriques. Dans un premier temps, nous extrayons les supports 2D de ces modules à partir d'un Modèle Numérique d' Elévation (MNE). Le résultat est un agencement de quadrilatères dont les éléments voisins sont connectés entre eux. Ensuite, nous reconstruisons les bâtiments en recherchant la configuration optimale de modèles 3D se fixant sur les supports précédemment extraits. Cette configuration correspond à la réalisation qui maximise une densité mesurant la cohérence entre la réalisation et le MNE, mais également prenant en compte des connaissances a priori telles que des lois d'assemblage des modules. Nous discutons enfin de la pertinence de cette approche en analysant les résultats obtenus à partir de données satellitaires (simulations PLEIADES). Des expérimentations sont également réalisées à partir d'images aériennes mieux résolues. |
|
top of the page
18 Conference articles |
1 - Building large urban environments from unstructured point data. F. Lafarge and C. Mallet. In Proc. IEEE International Conference on Computer Vision (ICCV), Barcelona, Spain, November 2011.
@INPROCEEDINGS{lafarge_iccv11,
|
author |
= |
{Lafarge, F. and Mallet, C.}, |
title |
= |
{Building large urban environments from unstructured point data}, |
year |
= |
{2011}, |
month |
= |
{November}, |
booktitle |
= |
{Proc. IEEE International Conference on Computer Vision (ICCV)}, |
address |
= |
{Barcelona, Spain}, |
pdf |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6126353}, |
keyword |
= |
{} |
} |
|
top of the page
These pages were generated by
|