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Spacetime Stereo: A Unifying Framework for Depth from Triangulation
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June 2003

James Davis, Ravi Ramamoorthi, Szymon Rusinkiewicz


Abstract

Depth from triangulation has traditionally been treated in a number of separate threads in the computer vision literature, with methods like stereo, laser scanning, and coded structured light considered separately. In this paper, we propose a common framework, spacetime stereo, that uni- fies many of these previous methods. Viewing specific techniques as special cases of this general framework leads to insights regarding the solutions to many of the traditional problems of individual techniques. Specifically, we discuss a number of innovative possible applications such as improved recovery of static scenes under variable illumination, spacetime stereo for moving objects, structured light and laser scanning with multiple simultaneous stripes or patterns, and laser scanning of shiny objects. To suggest the practical utility of the framework, we use it to analyze one of these applications recovery of static scenes under variable, but uncontrolled, illumination. 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.

Citation (BibTeX)

James Davis, Ravi Ramamoorthi, and Szymon Rusinkiewicz. Spacetime Stereo: A Unifying Framework for Depth from Triangulation. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 359-366, June 2003.

Paper
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Poster
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Links
  Paper's page at Stanford
  Extended version as a technical report
  Followup journal paper