Kalman filtering based object tracking in surveillance video system

Khoong, W. L. and Kow, W. Y. and Tan, H. T and Yoong, H. P and Teo, Kenneth Tze Kin (2011) Kalman filtering based object tracking in surveillance video system. In: Proceedings of the 3rd (2011) CUTSE International Conference, 8-9 November, 2011, Miri, Sarawak, Malaysia.


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In the field of motion estimation for surveillance video, various techniques have been applied. One of the common approaches is Kalman filtering technique and it is interesting to explore the extension of this technique for the prediction and estimation of motion via the image sequences. In this paper, a moving object tracking in surveillance video using Kalman filter is proposed. The typical Kalman filter is good in tracking the position of a moving object. However, when dealing with occlusion, the typical Kalman filter is not able to keep tracking and predicting the position of the occluded moving object. During occlusion, the information of moving object is not available for detection and tracking. The lacking of occlusion scene determination and prediction ability cause the existing Kalman filter fails in tracking occluded object. Besides that, in the case of tracking multiple moving objects, existing Kalman filter will experience difficulties to identify the respective objects. Therefore, in order to encounter these problems, an object tracking method using enhanced Kalman filter will be developed. The ability of tracking occluded moving object will be added to increase the efficiency during tracking. Furthermore, object recognition feature will be added too to increase the accuracy of the object tracking system.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Kalman filter, Object tracking, Surveillance system
Subjects: Q Science > QA Mathematics
?? TK8300-8360 ??
Divisions: SCHOOL > School of Engineering and Information Technology
Depositing User: Unnamed user with email storage.bpmlib@ums.edu.my
Date Deposited: 12 Jul 2012 04:18
Last Modified: 09 Nov 2017 07:39
URI: http://eprints.ums.edu.my/id/eprint/4548

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