3D Tracking using particle filters

Abstract

Recently, Particle filter has been used for numerous 3D tracking applications especially nonlinear tracking applications which are intractable using Kalman filter or other linear estimator. Particle filter approximates system's dynamics using weighted samples; therefore it can work with variety of systems. In the literature, particle filter is mostly used for articulated body tracking, gesture recognition and robot tracking. Although other applications exist, these are the dominant ones. This paper discusses 3D object tracking using particle filters. Three main particle filtering algorithms have been discussed in this paper and their performances have been evaluated using RMSE performance measure.