Reconstructing a 3-D scene from more than one camera is a classical
problem in computer vision. One of the major sources of diculty is the
fact that not all scene elements are visible from all cameras. In the last
few years, two promising approaches have been developed [11, 12] that
formulate the scene reconstruction problem in terms of energy minimization,
and minimize the energy using graph cuts. These energy minimization
approaches treat the input images symmetrically, handle visibility
constraints correctly, and allow spatial smoothness to be enforced. However,
these algorithm propose dierent problem formulations, and handle
a limited class of smoothness terms. One algorithm [11] uses a problem
formulation that is restricted to two-camera stereo, and imposes smoothness
between a pair of cameras. The other algorithm [12] can handle an
arbitrary number of cameras, but imposes smoothness only with respect
to a single camera. In this paper we give a more general energy minimization
formulation for the problem, which allows a larger class of spatial
smoothness constraints. We show that our formulation includes both of
the previous approaches as special cases, as well as permitting new energy
functions. Experimental results on real data with ground truth are also
included.