Applying temporal constraints to the dynamic stereo problem

Abstract An algorithm is presented for the problem of the stereopsis of time-varuing images (the dynamic stereo problem). Dynamic stereopsis is the integration of two problems; static stereopsis and temporal correspondence. Rather than finding the intersection of these problems to be more difficult, it was found that by solving the two problem simultaneously, and thus incorporating the spatio-temporal context within which a scene exists, some of the hard subproblems belonging to stereopsis and temporal correspondence could be avoided. The algorithm relies on a general smoothness assumption to assign both disparity and temporal matches. A simple model of the motion of three-dimensional features is used to guide the matching process and to identify conditional matches which violate a general smoothness assumption. A spatial proximity rule is used to further restrict possible matches. The algorithm has been tested on both synthetic and real input sequences. Input sequences were chosen from three-dimensional moving light displays and from “real” grey-level digitized images.