Creating multi-layered 3D images using reversible jump MCMC algorithms

Sergio Hernandez-Marin, Andrew M. Wallace, Gavin J. Gibson

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

4 Citations (Scopus)

Abstract

Standard 3D ranging and imaging systems process only a single return from an assumed single opaque surface. However, there are situations when the laser return consists of multiple peaks due to the footprint of the beam impinging on a target with surfaces distributed in depth or with semi-transparent surfaces. If all these returns are processed, a more informative multi-layered 3D image is created. We propose a unified theory of pixel processing for ladar data using a Bayesian approach that incorporates spatial constraints through a Markov Random Field. The different parameters of the several returns are estimated using reversible jump Markov chain Monte Carlo (RJMCMC) techniques in combination with an adaptive strategy of delayed rejection to improve the estimates of the parameters. © Springer-Verlag Berlin Heidelberg 2006.

Original languageEnglish
Title of host publicationAdvances in Visual Computing
Subtitle of host publicationSecond International Symposium, ISVC 2006 Lake Tahoe, NV, USA, November 6-8, 2006. Proceedings, Part II
Pages405-416
Number of pages12
Volume4292
ISBN (Electronic)978-3-540-48627-5
DOIs
Publication statusPublished - 2006
Event2nd International Symposium on Visual Computing - Lake Tahoe, NV, United States
Duration: 6 Nov 20068 Nov 2006

Publication series

NameLecture Notes in Computer Science
Volume4292
ISSN (Print)0302-9743

Conference

Conference2nd International Symposium on Visual Computing
Abbreviated titleISVC 2006
CountryUnited States
CityLake Tahoe, NV
Period6/11/068/11/06

Keywords

  • 3D ranging and imaging
  • Burst illumination laser
  • Markov random fields
  • Multi-layered image
  • Reversible jump Markov chain Monte Carlo
  • Time-correlated single photon counting

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