Region-Of-Interest Tracking
Short description
This tracking method relies on a statistical similarity measure in high dimension between
a Region-Of-Interest (user-)defined in a keyframe (the reference ROI) and
the regions potentially corresponding to it in subsequent frames.
In a given frame, the region minimizing the similarity measure with respect to the reference ROI
among admissible target regions is selected. Admissible regions are obtained by transforming the
bounding box of the reference ROI according to a chosen motion model, e.g., translation
and scaling.
The similarity measure is the Kullback-Leibler divergence between the multivariate feature PDF
of the reference ROI and the one of a target region. Its estimation relies on k-th nearest
neighbors. This allows to define features of high dimension combining radiometry (color, patches,
gradient…) and geometry (see CVPR 2007 on the page
Conferences and IEEE TIP 2009 on the page
Journals for complete references and preprint).
Illustrative result
