Object detection and tracking using the particle filtering

In this paper, we present a method for detecting and tracking rigid moving objects in a monocular image sequence. The originality of this method lies in a state modelling of this estimation problem which is solved in an unified way. This hybrid estimation problem leads to nonlinear state equations that are solved by the particle filtering. A particle filter is set for each shape model (modes). It estimates the motion and position parameters, tracks the object in the sequence and also computes at each time the probability of all modes.