Description: Particle filters are often used for tracking objects within a
scene. As the prediction model of a particle filter is often
implemented using basic movement predictions such as ran-
domwalk,constantvelocityoracceleration,thesemodelswill
usually be incorrect. Therefore, this paper proposes a new
approach, based on a Canonical Correlation Analysis (CCA)
tracking method which provides an object specific motion
model. This model is used to construct a proposal distribu-
tion of the prediction model which predicts new states, in-
creasing the robustness of the particle filter. Results confirm
anincreaseinaccuracycomparedtostate-of-the-artmethods.
To Search:
File list (Check if you may need any files):
paper_VCIP12_25_final_final.pdf
Download