2 Institute of Mathematics, University of Lübeck, Wallstraße 40, 23560 Lübeck, Germany,
papenber@ math. uni-luebeck. de Summary Optic flow describes the displacement field in
an image sequence. Its reliable computation constitutes one of the main challenges in
computer vision, and variational methods belong to the most successful techniques for
achieving this goal. Variational methods recover the optic flow field as a minimiser of a
suitable energy functional that involves data and smoothness terms. In this paper we present …

Optic fow describes the displacement field in an image sequence. Its reliable computation
constitutes one of the main challenges in computer vision, and variational methods belong
to the most successful techniques for achieving this goal. Variational methods recover the
optic flow field as a minimiser of a suitable energy functional that involves data and
smoothness terms. In this paper we present a survey on different model assumptions for
each of these terms and illustrate their impact by experiments. We restrict ourselves to …