The Panum Proxy Algorithm for Dense Stereo Matching over a Volume of Interest

Proceedings of the IEEE International Conference on Computer Vision & Pattern Recognition |

Stereo matching algorithms conventionally match over a
range of disparities sufficient to encompass all visible 3D
scene points. Human vision however does not do this. It
works over a narrow band of disparities — Panum’s fusional
band — whose typical range may be as little as 1/20
of the full range of disparities for visible points. Points inside
the band are fused visually and the remainder of points
are seen as “diplopic” — that is with double vision. The
Panum band restriction is important also in machine vision,
both with active (pan/tilt) cameras, and with high resolution
cameras and digital pan/tilt.
A probabilistic approach is presented for dense stereo
matching under the Panum band restriction. First it is
shown that existing dense stereo algorithms are inadequate
in this problem setting. Secondly it is shown that the main
problem is segmentation, separating the (left) image into
the areas that fall respectively inside and outside the band.
Thirdly, an approximation is derived that makes up for missing
out-of-band information with a “proxy” based on image
autocorrelation. Lastly it is shown that the Panum Proxy
algorithm achieves accuracy close to what can be obtained
when the full disparity band is available.