Generalized Multi-camera Scene Reconstruction Using Graph Cuts

Vladimir Kolmogorov, Ramin Zabih and Steven Gortler.

In Fourth International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), July 2003.


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.