Object Detection and Tracking

An improved object tracking algorithm based Kalman filtering is developed in this thesis. The algorithm uses a median filter and morphological operations during tracking. The problem created by object shadows is identified and the primary focus is to incorporate shadow detection and removal to improve tracking multiple objects in complex scenes. It is shown that the Kalman filter, without the improvements, fails to remove shadows that connect different objects. The application of the median filter helps the separation of different objects and thus enables the tracking of multiple objects individually. The performances of the Kalman filter and the improved tracking algorithm were tested on a highway video sequence of moving cars and it is shown that the proposed algorithm yields better performance in the presence of shadows