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.

@article{Davis:2005:SS:,
   author = "James Davis and Diego Nehab and Ravi Ramamoorthi and Szymon Rusinkiewicz",
   title = "{Spacetime Stereo}: A Unifying Framework for Depth from Triangulation",
   journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)",
   year = "2005",
   month = feb,
   volume = "27",
   number = "2",
   pages = "296--302"
}