Foreground segmentation and tracking based on foreground and background modeling techniques

The Project Framework is the detection and tracking of foreground objects in static and moving video sequences. The objective of a foreground segmentation and Tracking is to segment the scene in foreground objects and background and establish the temporal correspondence of the foreground objects. In this project we will focus on techniques that are based on a classification using a statistical model of the background and the foreground. For this reason, we will assume that the segmentation of the first frame is provided. Our objective will be to improve the models and define an appropriate updating of these models to reach a correct foreground-background segmentation minimizing False Negatives and False Positives. The tracking process makes the correspondence of the segmented objects with the objects being tracked from previous frames. Depending on the technique, the tracking can be clearly separated from the segmentation (when previous foreground information is not used for the segmentation) or can be implicit in the foreground segmentation (when we are using a priori information of the object)