<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Csaba Benedek</style></author><author><style face="normal" font="default" size="100%">Tamas Sziranyi</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author><author><style face="normal" font="default" size="100%">Josiane Zerubia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Detection of Object Motion Regions in Aerial Image Pairs with a Multilayer Markovian Model</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE TRANSACTIONS ON IMAGE PROCESSING</style></secondary-title><short-title><style face="normal" font="default" size="100%">IEEE T IMAGE PROCESS</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">2303 - 2315</style></pages><isbn><style face="normal" font="default" size="100%">1057-7149</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We propose a new Bayesian method for detectingthe regions of object displacements in aerial image pairs. We use a robust but coarse 2-D image registration algorithm. Our main challenge is to eliminate the registration errors from the extracted change map. We introduce a three-layer Markov Random Field (L3MRF) model which integrates information from two different features, and ensures connected homogenous regions in the segmented images. Validation is given on real aerial photos.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><work-type><style face="normal" font="default" size="100%">Journal article</style></work-type><notes><style face="normal" font="default" size="100%">UT: 000269715500013ScopusID: 70349442338doi: 10.1109/TIP.2009.2025808</style></notes></record></records></xml>