Spacetime stereo: A unifying framework for depth from triangulation

James Davis, Diego Nehab, Ravi Ramamoorthi, Szymon M. Rusinkiewicz

Research output: Contribution to journalArticle

222 Scopus citations

Abstract

Depth from triangulation has traditionally been investigated in a number of independent threads of research, with methods such as stereo, laser scanning, and coded structured light considered separately. In this paper, we propose a common framework called spacetime stereo that unifies and generalizes many of these previous methods. To show the practical utility of the framework, we develop two new algorithms for depth estimation: depth from unstructured illumination change and depth estimation in dynamic scenes. Based on our analysis, we show that methods derived from the spacetime stereo framework can be used to recover depth in situations in which existing methods perform poorly.

Original languageEnglish (US)
Pages (from-to)296-302
Number of pages7
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume27
Issue number2
DOIs
StatePublished - Feb 1 2005

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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