@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 =	 {}
}