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Exploiting Spatio-Temporal Information for Light-Plane Labeling in Depth-Image Sensors Using Probabilistic Graphical Models
Volume 27, Issue 1 (2016), pp. 67–84
Jaka Kravanja   Mario Žganec   Jerneja Žganec-Gros   Simon Dobrišek   Vitomir Štruc  

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https://doi.org/10.15388/Informatica.2016.77
Pub. online: 1 January 2016      Type: Research Article     

Received
1 March 2014
Accepted
1 April 2015
Published
1 January 2016

Abstract

This paper proposes a novel approach to light plane labeling in depth-image sensors relying on “uncoded” structured light. The proposed approach adopts probabilistic graphical models (PGMs) to solve the correspondence problem between the projected and the detected light patterns. The procedure for solving the correspondence problem is designed to take the spatial relations between the parts of the projected pattern and prior knowledge about the structure of the pattern into account, but it also exploits temporal information to achieve reliable light-plane labeling. The procedure is assessed on a database of light patterns detected with a specially developed imaging sensor that, unlike most existing solutions on the market, was shown to work reliably in outdoor environments as well as in the presence of other identical (active) sensors directed at the same scene. The results of our experiments show that the proposed approach is able to reliably solve the correspondence problem and assign light-plane labels to the detected pattern with a high accuracy, even when large spatial discontinuities are present in the observed scene.

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Vilnius University

Keywords
depth images structured light probabilistic graphical models spatio-temporal information

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INFORMATICA

  • Online ISSN: 1822-8844
  • Print ISSN: 0868-4952
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