**Jenkin and
Tsotsos 1986 :** An
algorithm is presented for the problem of the stereopsis of time-varying 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.