Enumerate! Don't Estimate.
Shai Avidan
(Tel Aviv U., Isreael)
Abstract:
However estimation is difficult because of noise in the measurements, missing
data and outliers. On top of that, it is not always possible to give global
guarantees for the estimated solution. Enumeration, on the other hand, is
simple. It requires going through all possible hypotheses, evaluating them one
by one and reporting the best one. The key is to prove that there is an
efficient way to enumerate all possible hypotheses. I will show a couple of
applications that find a guranteed approximation to the global optimum for a
number of computer vision problems including 2D affine template matching and 3D
symmetry detection.
Joint work with Simon Korman, Roee Litman, Daniel Reichman, Gilad Tsur and Alex
Bronstein.