Calculus of Variations and Geometric Measure Theory

E. Bardelli - M. Colombo - A. C. G. Mennucci - A. Yezzi

Multiple Object Tracking via Prediction and Filtering with a Sobolev-type Metric on Curves

created by mennucci on 18 Aug 2012
modified on 14 Nov 2012


Published Paper

Inserted: 18 aug 2012
Last Updated: 14 nov 2012

Journal: Fifth Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment (NORDIA'12)
Pages: 10
Year: 2012

October 7, 2012, Firenze, Italy (in conjunction with ECCV 2012)

Links: conference page, open source code implementing the paper algorithms


The problem of multi-target tracking of deforming objects in video sequences arises in many situations in image processing and computer vision. Many algorithms based on finite dimensional particle filters 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 predictions 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 tracking 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.