Recent variational stereo approaches suffer from at least one of the
following drawbacks: Either they use an isotropic disparity-driven
smoothness term that ignores the directional information of the
disparity field, or they apply anisotropic image-driven regularisation
that suffers from oversegmentation artifacts. As a remedy, we present a
novel anisotropic disparity-driven approach for stereo vision. Its
directional adaptation allows to better control the smoothing w.r.t. the
local structure of the disparity field. Experiments that compare our
model to a recent isotropic variational method demonstrate the superior
quality of our approach.