@inproceedings {Perse2004a, title = {Vrednotenje u\v{c}inkovitosti Kalmanovega filtra pri sledenju ljudi}, abstract = {Kalman filtering (KF) is a standard technique for estimating position and uncertainty of a moving object based on noisy measurements and knowledge of object dynamics. In this paper we apply the Kalman filter algorithm to estimate the motion parameters (position and speed) of a moving Per\v{s}on from a video stream. To assess the efficiency of KF tracking various experiments with and without KF were performed. The results showed that modeling of a Per\v{s}on motion and measurement noise using KF algorithm can considerably improve the tracking performance in cases of human interactions and occlusions.}, author = {M. Per\v{s}e and Janez Per\v{s} and Matej Kristan and Stanislav Kovacic}, month = {Sep}, pages = {191-194}, year = {2004}, booktitle = {Proceedings of the thirteenth Electrotechnical and Computer Science Conference} }