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PHD Filter Multi-Target Tracking Demonstrations

Here we demonstrate some examples of tracking with Probability Hypothesis Density (PHD) filters on both simulated and real data to illustrate the ability of these algorithms to identify (detect) targets, initiate tracks and terminate them when targets leave the scene. The number of targets varies over time and the algorithms also estimate the number of targets. This is in the presence of clutter (false alarms), where there are many more false measurements than those generated by true targets. The tracking videos are grouped into different sections according to the implementation or application. These are grouped as follows:

Gaussian mixture PHD Filter

GM-(C)PHD filter tracking |   Sonar |   Video |   Radar


Tracking football players |   People Tracking

Tracking Footballer Players

The first example is of tracking football players from one team (white shirts) in a video sequence. We can see that the players from this team are identified when they enter the camera feld of view. (Video courtesy of the National University of Singapore).

Tracking People in Video

The second example demonstrates the PHD filter in an outdoor environment with a fixed camera. (Video courtesy of the National University of Singapore).

Heriot-Watt University and the University of Melbourne 2008