TY  - JOUR
T1  - Experimental Analysis of Object Tracking During Occlusion
AU - Ong, Lee-Yeng AU - Lau, Siong Hoe AU - Koo, Voon Chet AU - Khoo, Xin Ping 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 4
SP  - 820
EP  - 826
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.820.826
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.820.826
KW  - Object tracking
KW  -occlusion
KW  -Kalman filter
KW  -video surveillance
KW  -conventional predicted motion
KW  -verify the performance
AB  - 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.
ER  -