2 research outputs found
Multiple Object Tracking via Prediction and Filtering with a Sobolev-Type Metric on Curves
The problem of multi-target tracking of deforming objects in
video sequences arises in many situations in image processing and com-
puter vision. Many algorithms based on finite dimensional particle fil-
ters have been proposed. Recently, particle filters for infinite dimensional
Shape Spaces have been proposed although predictions are restricted to
a low dimensional subspace. We try to extend this approach using pre-
dictions in the whole shape space based on a Sobolev-type metric for
curves which allows unrestricted infinite dimensional deformations. For
the measurement model, we utilize contours which locally minimize a
segmentation energy function and focus on the multiple contour track-
ing framework when there are many local minima of the segmentation
energy to be detected. The method detects figures moving without the
need of initialization and without the need for prior shape knowledge of
the objects tracked