Non-linear matched filtering for object detection and tracking
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 non-linear state equations that are solved by the particle method. A particle filter is set for each shape model (modes). It estimates the motion and position parameters and tracks the object in the sequence. The algorithm also computes at each time the probability of all modes. This method is then applied to synthetic and real image sequences in order to evaluate the estimation accuracies and the robustness of the tracking procedure.
detection and tracking hybrid estimation particle filtering motion analysis