<?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%">Alessandro Vianello</style></author><author><style face="normal" font="default" size="100%">Giulio Manfredi</style></author><author><style face="normal" font="default" size="100%">Maximilian Diebold</style></author><author><style face="normal" font="default" size="100%">Bernd Jähne</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">3D reconstruction by a combined structure tensor and Hough transform light field approach</style></title><secondary-title><style face="normal" font="default" size="100%">tm - Technisches Messen</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Disparity estimation using the structure tensor is a local approach to determine orientation in Epipolar Plane Images. A global extension would lead to more precise and robust estimations. In this work, a novel algorithm for 3D reconstruction from linear light fields is proposed. This method uses a modified version of the Progressive Probabilistic Hough Transform to extract orientations from Epipolar Plane Images, allowing to achieve high quality disparity maps. To this aim, the structure tensor estimates are used to speed up computation and improve the disparity estimation near occlusion boundaries. The new algorithm is evaluated on both synthetic and real light field datasets, and compared with classical local disparity estimation techniques based on the structure tensor.</style></abstract></record></records></xml>