<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jens Schmuedderich</style></author><author><style face="normal" font="default" size="100%">Volker Willert</style></author><author><style face="normal" font="default" size="100%">Julian Eggert</style></author><author><style face="normal" font="default" size="100%">Sven Rebhan</style></author><author><style face="normal" font="default" size="100%">Christian Goerick</style></author><author><style face="normal" font="default" size="100%">Gerhard Sagerer</style></author><author><style face="normal" font="default" size="100%">Edgar Koerner</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimating object proper motion using optical flow, kinematics, and depth information.</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Trans Syst Man Cybern B Cybern</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CoR-Lab Publication</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">August</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1109/TSMCB.2008.925657</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">38</style></volume><pages><style face="normal" font="default" size="100%">1139Ã¢â‚¬â€œ1151</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;For the interaction of a mobile robot with a dynamic environment, the estimation of object motion is desired while the robot is walking and/or turning its head. In this paper, we describe a system which manages this task by combining depth from a stereo camera and computation of the camera movement from robot kinematics in order to stabilize the camera images. Moving objects are detected by applying optical flow to the stabilized images followed by a filtering method, which incorporates both prior knowledge about the accuracy of the measurement and the uncertainties of the measurement process itself. The efficiency of this system is demonstrated in a dynamic real-world scenario with a walking humanoid robot.&lt;/p&gt;</style></abstract></record></records></xml>