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3D Computer Vision: From Points to Concepts

  • Luís A. AlexandreEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9493)

Abstract

The emergence of cheap structured light sensors, like the Kinect, opened the door to an increased interest in all matters related to the processing of 3D visual data. Applications for these technologies are abundant, from robot vision to 3D scanning. In this paper we go through the main steps used on a typical 3D vision system, from sensors and point clouds up to understanding the scene contents, including key point detectors, descriptors, set distances, object recognition and tracking and the biological motivation for some of these methods. We present several approaches developed at our lab and some current challenges.

Keywords

Point Cloud Convolutional Neural Network Transfer Learning Scene Point Voxel Grid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Informatics and Instituto de TelecomunicaçõesUniversity of Beira InteriorCovilhãPortugal

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