Automatic pedestrian tracking using discrete choice models and image correlation techniques

Presenter's/Interviewee's Name: 
Gianluca Antonini, Signal Processing Institute

Your browser is not able to display this multimedia content.

Problems viewing videos?
Download latest Windows Media Player

In this paper we deal with the multi-object tracking problem, with specific reference to the visual tracking of pedestrians, assuming that the pedestrian-detection step is already done. We use a Bayesian framework to combine the visual information provided by a simple image correlation algorithm with a behavioral model ( discrete choice model ) for pedestrian dynamic, calibrated on real data. We aim to show how the combination of the image information with a model of pedestrian behavior can provide appreciable results in real and complex scenarios.