Flexible camera setup for visual based registration on 2D interaction surface with undefined geometry using neural network

Ary Setijadi Prihatmanto, Michael Haller, Roland Wagner

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

Camera setup, calibration and visual based registration of Augmented Reality (AR) based tabletop setups can be a really complicated and time-intensive task. Homography is often used liberally despite its assumption for planar surfaces, where the mapping from the camera to the table can be expressed by a simple projective homography. However, this approach often fails in curved and non-planar surface setups. In this paper, we propose a technique that approximates the values and reduces the tracking error-values by the usage of a neural network function. The final result gives a uniform representation of the camera against combinations of camera parameters that will help in the multi-camera setup. We present the advantages with demonstration applications, where a laser pointer spot and a light from the lamp will be tracked in non planar surface.

Original languageEnglish
Title of host publicationAdvances in Artificial Reality and Tele-Existence - 16th International Conference on Artificial Reality and Telexistence, ICAT 2006, Proceedings
Pages948-959
Number of pages12
DOIs
Publication statusPublished - 2006
Event16th International Conference on Artificial Reality and Telexistence, ICAT 2006 - Hangzhou, China
Duration: 29 Nov 20061 Dec 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4282 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Artificial Reality and Telexistence, ICAT 2006
Country/TerritoryChina
CityHangzhou
Period29.11.200601.12.2006

Keywords

  • Camera calibration
  • Function approximation
  • Neural network
  • Tabletop application
  • Visual based registration

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