<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Attila Tanacs</style></author><author><style face="normal" font="default" size="100%">András Majdik</style></author><author><style face="normal" font="default" size="100%">Levente Hajder</style></author><author><style face="normal" font="default" size="100%">Jozsef Molnar</style></author><author><style face="normal" font="default" size="100%">Zsolt Santa</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Chu-Song Chen</style></author><author><style face="normal" font="default" size="100%">Mohan Kankanhall</style></author><author><style face="normal" font="default" size="100%">Shang-Hong Lai</style></author><author><style face="normal" font="default" size="100%">Joo Hwee</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Collaborative Mobile 3D Reconstruction of Urban Scenes</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the ACCV Workshop on Intelligent Mobile and Egocentric Vision (ACCV-IMEV), Lecture Notes in Computer Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov 2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Singapore</style></pub-location><pages><style face="normal" font="default" size="100%">1-16</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zsolt Santa</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Michael Felsberg</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Affine Alignment of Occluded Shapes</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Pattern Recognition (ICPR)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Aug 2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Stockholm, Svédország</style></pub-location><pages><style face="normal" font="default" size="100%">2155-2160</style></pages><isbn><style face="normal" font="default" size="100%">978-4-9906441-0-9</style></isbn><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zsolt Santa</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Correspondence-less non-rigid registration of triangular surface meshes</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June 2013</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Portland, OR, USA</style></pub-location><pages><style face="normal" font="default" size="100%">2275 - 2282</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A novel correspondence-less approach is proposed to find a thin plate spline map between a pair of deformable 3D objects represented by triangular surface meshes. The proposed method works without landmark extraction and feature correspondences. The aligning transformation is found simply by solving a system of nonlinear equations. Each equation is generated by integrating a nonlinear function over the object's domains. We derive recursive formulas for the efficient computation of these integrals. Based on a series of comparative tests on a large synthetic dataset, our triangular mesh-based algorithm outperforms state of the art methods both in terms of computing time and accuracy. The applicability of the proposed approach has been demonstrated on the registration of 3D lung CT volumes. © 2013 IEEE.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">ScopusID: 84887348013doi: 10.1109/CVPR.2013.295</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zsolt Santa</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Geoff West</style></author><author><style face="normal" font="default" size="100%">Péter Kövesi</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Elastic Registration of 3D Deformable Objects</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of International Conference on Digital Image Computing: Techniques and Applications (DICTA)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov 2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.inf.u-szeged.hu/~kato/papers/dicta2012.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">New York</style></pub-location><pages><style face="normal" font="default" size="100%">1 - 7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A novel correspondence-less approach is proposed to find a non-linear aligning transformation between a pair of deformable 3D objects. Herein, we consider a polynomial deformation model, but our framework can be easily adapted to other common deformations. The basic idea of the proposed method is to set up a system of nonlinear equations whose solution directly provides the parameters of the aligning transformation. Each equation is generated by integrating a nonlinear function over the object's domains. Thus the number of equations is determined by the number of adopted nonlinear functions yielding a flexible mechanism to generate sufficiently many equations. While classical approaches would establish correspondences between the shapes, our method works without landmarks. The efficiency of the proposed approach has been demonstrated on a large synthetic dataset as well as in the context of medical image registration.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">UT: 000316318400010doi: 10.1109/DICTA.2012.6411674</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zsolt Santa</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Paulo de Souza</style></author><author><style face="normal" font="default" size="100%">Ulrich Engelke</style></author><author><style face="normal" font="default" size="100%">Ashfaqur Rahman</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Pose Estimation of Ad-hoc Mobile Camera Networks</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Digital Image Computing: Techniques and Applications (DICTA)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Hobart, TAS </style></pub-location><pages><style face="normal" font="default" size="100%">88 - 95</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;article&quot;&gt;&lt;p&gt;An algorithm is proposed for the pose estimation of ad-hoc mobile camera networks with overlapping views. The main challenge is to estimate camera parameters with respect to the 3D scene without any specific calibration pattern, hence allowing for a consistent, camera-independent world coordinate system. The only assumption about the scene is that it contains a planar surface patch of a low-rank texture, which is visible in at least two cameras. Such low-rank patterns are quite common in urban environments. The proposed algorithm consists of three main steps: relative pose estimation of the cameras within the network, followed by the localization of the network within the 3D scene using a low-rank surface patch, and finally the estimation of a consistent scale for the whole system. The algorithm follows a distributed architecture, hence the computing power of the participating mobile devices are efficiently used. The performance and robustness of the proposed algorithm have been analyzed on both synthetic and real data. Experimental results confirmed the relevance and applicability of the method.&lt;/p&gt;&lt;/div&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><accession-num><style face="normal" font="default" size="100%">14000303 </style></accession-num></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zsolt Santa</style></author><author><style face="normal" font="default" size="100%">Zoltan Kato</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Unifying Framework for Non-linear Registration of 3D Objects</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE International Conference on Cognitive Infocommunications (CogInfoCom)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec 2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.inf.u-szeged.hu/~kato/papers/coginfocomm2012.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Kosice, Slovakia </style></pub-location><pages><style face="normal" font="default" size="100%">547 - 552</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4673-5187-4 </style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;article&quot;&gt;&lt;p&gt;An extension of our earlier work is proposed to find a &lt;span class=&quot;snippet&quot;&gt;non&lt;/span&gt;-&lt;span class=&quot;snippet&quot;&gt;linear&lt;/span&gt; aligning transformation between a pair of deformable &lt;span class=&quot;snippet&quot;&gt;3D&lt;/span&gt; &lt;span class=&quot;snippet&quot;&gt;objects&lt;/span&gt;. The basic idea is to set up a system of nonlinear equations whose solution directly provides the parameters of the aligning transformation. Each equation is generated by integrating a nonlinear function over the &lt;span class=&quot;snippet&quot;&gt;object&lt;/span&gt;'s domains. Thus the number of equations is determined by the number of adopted nonlinear functions yielding a flexible mechanism to generate sufficiently many equations. While classical approaches would establish correspondences between the shapes, our method works without landmarks. Experiments with &lt;span class=&quot;snippet&quot;&gt;3D&lt;/span&gt; polynomial and thin plate spline deformations confirm the performance of the &lt;span class=&quot;snippet&quot;&gt;framework&lt;/span&gt;.&lt;/p&gt;&lt;/div&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">UT: 000320454200086</style></notes></record></records></xml>