@InProceedings{freedman:cvpr00,
author = {D.\ Freedman and M.\ S.\ Brandstein},
title = {Provably fast algorithms for contour tracking},
booktitle = {Computer Vision and Pattern Recognition,
2000. Proceedings. IEEE Conference on},
year = 2000,
volume = 1,
pages = {139--144},
keywords = {computational complexity, computer vision,
optimisation, complexity bounds, contour tracking,
global optimization problem, provably fast
algorithms, training curves},
abstract = {A new tracker is presented. Two sets are identified:
one which contains all possible curves as found in
the image, and a second which contains all curves
which characterize the object of interest. The
former is constructed out of edge-points in the
image, while the latter is learned prior to
running. The tracked curve is taken to be the
element of the first set which is nearest the second
set. The formalism for the learned set of curves
allows for mathematically well understood groups of
transformations (e.g. affine, projective) to be
treated on the same footing as less well understood
deformations, which may be learned from training
curves. An algorithm is proposed to solve the
tracking problem, and its properties are
theoretically demonstrated: it solves the global
optimization problem, and does so with certain
complexity bounds. Experimental results applying the
proposed algorithm to the tracking of a moving
finger are presented, and compared with the results
of a condensation approach},
annote = {}
}