Multiple object tracking under heavy occlusions by using Kalman filters based on shape matching

This paper describes a technique for tracking single objects moving within the guarded scene during dynamic occlusion situations. The processing modules used for object detection and tracking will be shown in detail and the performances of the algorithm discussed. The proposed approach uses an empty reference image for object extraction through image difference; the reference frame is updated continuously by a background updating module taking into account the detected objects. The tracking module is responsible for objects labeling being able to preserve objects identity even when an overlapping occurs on the image plane between different objects. A shape matching technique is used that is based on a linear Kalman filter. The system has been tested on several outdoor sequences showing dynamic occlusions among objects in order to show the validity of the approach.