GPAPF: A Combined Approach for 3D Body Part Tracking

Abstract

In this paper we present a combined approach for body part tracking in 3D using multiple cameras, called GPAPF. This approach combines annealed particle filtering, which has been shown as effective tracker for body parts, with Gaussian Process Dynamical Model, which is used in order to reduce the dimensionality of the problem. That reduction improves the tracker's performance and increases the tracker's stability and ability to recover from the loosing the target. We also compare GPAPF tracker with the annealed particle filter and show that our tracker has a better performance even for low frame rate sequences.