DOI:10.29111/ijlrst ISRA Impact Factor:3.35, Peer-reviewed, Open-access Journal
Research Paper Open Access
International Journal of Latest Research in Science and Technology Vol.3 Issue 2, pp 197-200,Year 2014
Correspondence should be addressed to :
Received : 24 April 2014; Accepted : 27 April 2014 ; Published : 30 April 2014
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Vision based surveillance system plays an important role in security field. Automatic tracking of objects such as human and vehicle is vital in such a system. In human tracking, it frequently happens that moving people get merged and demerged. When merging occurs, the tracking system should know what and how many humans are in the cluster. When cluster gets demerged into individuals, the tracking system should be able to differentiate among them to cope with correct human following. It will be useful in tracking if we can enforce the human cluster, where multiple humans adhere, to be broken into individual human. In this paper, we propose a novel method for individualization of human cluster in tracking. The method consists of three steps. They are edge finding and edge projection, mixture of Gaussian fitting, and cutting point decision. We applied the method to various scenarios of human cluster and obtained good results.
Copyright © 2014 Youngsung Soh et al. This is an open access article distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Youngsung Soh, Yongsuk Hae, Hadi Ashraf, Mudasar Qadir, Intaek Kim , " Enforced Individualization Of Human Cluster In Tracking By Mixture Of Gaussian ", International Journal of Latest Research in Science and Technology . Vol. 3, Issue 2, pp 197-200 , 2014
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