|
Publications de Jean-Guy Boureau
Résultat de la recherche dans la liste des publications :
Article de conférence |
1 - 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
Ces pages sont générées par
|