  In [18], Mozerov et al. propose to perform stereo matching as a two-step
energy minimization problem. For the first step they solve a fully connected
MRF model. And in the next step the marginal output is employed as the unary
cost for a locally connected MRF model.
  In this paper we intend to combine the two steps of energy minimization in
order to improve stereo matching results. We observe that the fully connected
MRF leads to smoother disparity maps, while the locally connected MRF achieves
superior results in fine-structured regions. Thus we propose to jointly solve
the fully connected and locally connected models, taking both their advantages
into account. The joint model is solved by mean field approximations. While
remaining efficient, our joint model outperforms the two-step energy
minimization approach in both time and estimation error on the Middlebury
stereo benchmark v3.
