Abstract
Rotoscoping, the detailed delineation of scene elements
through a video shot, is a painstaking task of tremendous
importance in professional post-production pipelines. While
pixel-wise segmentation techniques can help for this task,
professional rotoscoping tools rely on parametric curves that
offer the artists a much better interactive control on the defi-
nition, editing and manipulation of the segments of interest.
Sticking to this prevalent rotoscoping paradigm, we propose
a novel framework to capture and track the visual aspect
of an arbitrary object in a scene, given a first closed outline of this object. This model combines a collection of local
foreground/background appearance models spread along the
outline, a global appearance model of the enclosed object
and a set of distinctive foreground landmarks. The structure
of this rich appearance model allows simple initialization,
efficient iterative optimization with exact minimization at
each step, and on-line adaptation in videos. We demonstrate
qualitatively and quantitatively the merit of this framework
through comparisons with tools based on either dynamic segmentation with a closed curve or pixel-wise binary labelling