Proceedings of the Second International Conference on Computer Vision Theory and Applications, Barcelona, İspanya, 8 - 11 Mart 2007, ss.13-20
Algorithmic 3D reconstruction methods like stereopsis or structure from motion fail to extract depth at homogeneous image structures where the human visual system succeeds and is able to estimate depth. In this
paper, using chromatic 3D range data, we analyze in which way depth in homogeneous structures is related to
the depth at the bounding edges. For this, we first extract the local 3D structure of regularly sampled points,
and then, analyze the coplanarity relation between these local 3D structures. We can statistically show that the
likelihood to find a certain depth at a homogeneous image patch depends on the distance between the image
patch and its edges. Furthermore, we find that this prediction is higher when there is a second edge which
is proximate to and coplanar with the first edge. These results allow deriving statistically based prediction
models for depth extrapolation into homogeneous image structures. We present initial results of a model that
predicts depth based on these statistics.