Lee-Yeng  Ong, Siong Hoe  Lau, Voon Chet  Koo, Xin Ping  Khoo, 
    Experimental Analysis of Object Tracking During Occlusion,
    Journal of Engineering and Applied Sciences,
    Volume 13,Issue 4,
    2018,
    Pages 820-826,
    ISSN 1816-949x,
    jeasci.2018.820.826,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2018.820.826)
    Abstract: Object tracking is an essential process for automating various video surveillance applications. In
order to obtain the trajectories of every moving objects in a scene, the tracking algorithm has to equip with the
ability in handling occlusion. Among the existing tracking algorithms, most of the researches used prediction
model to estimate the object’s trajectory of the consecutive frames. The estimated position serves as a reference
tool to detect and resolve occlusion. This study aims to analyze the performance of Kalman filter prediction
model during occlusion incident. Although, Kalman filter is widely applied for object tracking, less effort is done
on evaluating the parameter setting and its effect in long-term full occlusion. Experiments are conducted with
tracking datasets of varying velocity and acceleration. The experimental result is compared with a conventional
predicted motion model to verify the performance of Kalman filter during occlusion.
    Keywords: Object tracking;occlusion;Kalman filter;video surveillance;conventional predicted motion;verify the performance