<?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%">Meister, Stephan</style></author><author><style face="normal" font="default" size="100%">Izadi, Shahram</style></author><author><style face="normal" font="default" size="100%">Kohli, Pushmeet</style></author><author><style face="normal" font="default" size="100%">M Hämmerle</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">When can we use KinectFusion for ground truth acquisition?</style></title><secondary-title><style face="normal" font="default" size="100%">Proc Workshop on \ldots</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://meshlab.sourceforge.net/ http://www.msr-waypoint.net/en-us/um/people/pkohli/papers/mikhrk_iros_dataset_2012.pdf%5Cnpapers3://publication/uuid/2615CF9D-C632-4E39-B1C4-B32A4A5D339C</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">3–8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Abstract—KinectFusion is a method for real-time capture of dense 3D geometry of the physical environment using a depth sensor. The system allows capture of a large dataset of 3D scene reconstructions at very low cost. In this paper we discuss the properties of the ...$\backslash$n</style></abstract></record></records></xml>