|
|
Publications sur Energie d'attache aux données
Résultat de la recherche dans la liste des publications :
2 Articles de conférence |
1 - 2D and 3D Vegetation Resource Parameters Assessment using Marked Point Processes.
G. Perrin et X. Descombes et J. Zerubia. Dans Proc. International Conference on Pattern Recognition (ICPR), Hong-Kong, août 2006.
Mots-clés : Energie d'attache aux données, Extraction d'objets, Extraction de Houppiers, Geometrie stochastique, Processus ponctuels marques.
@INPROCEEDINGS{perrin_06_c,
|
| author |
= |
{Perrin, G. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{2D and 3D Vegetation Resource Parameters Assessment using Marked Point Processes}, |
| year |
= |
{2006}, |
| month |
= |
{août}, |
| booktitle |
= |
{Proc. International Conference on Pattern Recognition (ICPR)}, |
| address |
= |
{Hong-Kong}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2006_perrin_06_c.pdf}, |
| keyword |
= |
{Energie d'attache aux données, Extraction d'objets, Extraction de Houppiers, Geometrie stochastique, Processus ponctuels marques} |
| } |
Abstract :
High resolution aerial and satellite images of forests have a key role to play in natural resource management. As they enable to study forests at the scale of trees, it is now possible to get a more accurate evaluation of the forest resources, from which can be deduced information of biodiversity and ecological sustainability. In that prospect, automatic algorithms are needed to give a further exploitation of the data and to assist human operators. In this paper, we present a stochastic geometry approach to extract 2D and 3D parameters of the trees, by modelling the stands as some realizations of a marked point process of ellipses or ellipsoids, whose points are the positions of the trees and marks their geometric features. This approach gives also the number of stems, their position, and their size. It is an energy minimization problem, where the energy embeds a regularization term (prior density), which introduces some interactions between the objects, and a data term, which links the objects to the features to be extracted. Results are shown on aerial images provided by the French National Forest Inventory (IFN). |
|
2 - Forest Resource Assessment using Stochastic Geometry.
G. Perrin et X. Descombes et J. Zerubia et J.G. Boureau. Dans Proc. International Precision Forestry Symposium, mars 2006.
Mots-clés : Extraction de Houppiers, Extraction d'objets, Geometrie stochastique, RJMCMC, Energie d'attache aux données.
@INPROCEEDINGS{perrin_06_b,
|
| author |
= |
{Perrin, G. and Descombes, X. and Zerubia, J. and Boureau, J.G.}, |
| title |
= |
{Forest Resource Assessment using Stochastic Geometry}, |
| year |
= |
{2006}, |
| month |
= |
{mars}, |
| booktitle |
= |
{Proc. International Precision Forestry Symposium}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/perrin_ipfs06.pdf}, |
| keyword |
= |
{Extraction de Houppiers, Extraction d'objets, Geometrie stochastique, RJMCMC, Energie d'attache aux données} |
| } |
Abstract :
Aerial and satellite imagery has a key role to play in natural resource management, especially in forestry application. The submetric resolution of the data enables to study forests at the scale of trees, and to get a more accurate assessment of the resources such as the number of stems or the forest cover. To develop automatic tools in order to help the inventories in their work and to bring more knowledge about the stands is also nowadays of important economical and environmental concerns.
In this paper, we aim at extracting tree crowns from high resolution aerial Color Infrared images (CIR) of forests using marked point processes. Our approach consists in modelling the trees in the forestry images as random configurations of ellipses, whose points are the positions of the stems and marks their geometric features. The density of this process embeds a regularization term (prior density), which introduces some interactions between the objects, and a data term, which links the objects to the features to be extracted. Our goal is to find the best configuration of an unknown number of objects, i.e. the configuration that maximizes this density. To sample this marked point process, we use Monte Carlo dynamics while the optimization is performed via a Simulated Annealing algorithm, which results in a fully automatic approach.
We present different models for the data term in order to cope with different kinds of stands : plantations, isolated trees and mixed stands. Results are shown on aerial CIR images provided by the French Forest Inventory (IFN) |
|
 haut de la page
Rapport de recherche et Rapport technique |
1 - A Non-Bayesian Model for Tree Crown Extraction using Marked Point Processes.
G. Perrin et X. Descombes et J. Zerubia. Rapport de Recherche 5846, INRIA, France, février 2006.
Mots-clés : Energie d'attache aux données, Extraction d'objets, Extraction de Houppiers, Processus ponctuels marques, Geometrie stochastique, Reconstruction en 3D.
@TECHREPORT{rr_perrin_nonbay_05,
|
| author |
= |
{Perrin, G. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A Non-Bayesian Model for Tree Crown Extraction using Marked Point Processes}, |
| year |
= |
{2006}, |
| month |
= |
{février}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{5846}, |
| address |
= |
{France}, |
| url |
= |
{http://hal.inria.fr/inria-00070180/fr/}, |
| pdf |
= |
{http://hal.inria.fr/inria-00070180/fr/}, |
| keyword |
= |
{Energie d'attache aux données, Extraction d'objets, Extraction de Houppiers, Processus ponctuels marques, Geometrie stochastique, Reconstruction en 3D} |
| } |
Résumé :
Dans ce rapport de recherche, notre but est d'extraire les houppiers à partir d'images aériennes de forêts à l'aide de processus ponctuels marqués d'ellipses ou d'ellipsoïdes. Notre approche consiste, en effet, à modéliser les données comme des réalisations de tels processus. Une fois l'objet géométrique de référence choisi, nous échantillonnons le processus objet défini par une densité grâce à un algorithme MCMC à sauts réversibles, optimisé par un recuit simulé afin d'extraire la meilleure configuration d'objets, qui nous donne l'extraction recherchée.
Nous obtenons ainsi le nombre des arbres, leur localisation et leur taille. Nous présentons, dans ce rapport, un modèle 2D et un modèle 3D pour extraire des statistiques forestières. Ceux-ci sont testés sur des images aériennes infrarouge couleur très haute résolution fournies par l'Inventaire Forestier National (IFN). |
Abstract :
High resolution aerial and satellite images of forests have a key role to play in natural resource management. As they enable forestry managers to study forests at the scale of trees, it is now possible to get a more accurate evaluation of the resources. Automatic algorithms are needed in that prospect to assist human operators in the exploitation of these data. In this paper, we present a stochastic geometry approach to extract 2D and 3D parameters of the trees, by modelling the stands as some realizations of a marked point process of ellipses or ellipsoids, whose points are the locations of the trees and marks their geometric features. As a result we obtain the number of stems, their position, and their size. This approach yields an energy minimization problem, where the energy embeds a regularization term (prior density), which introduces some interactions between the objects, and a data term, which links the objects to the features to be extracted, in 2D and 3D. Results are shown on Colour Infrared aerial images provided by the French National Forest Inventory (IFN) |
|
haut de la page
Ces pages sont générées par 
|
Nouvelle page de démos
bibtex
