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People detection and tracking under occlusion

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dc.contributor.advisor Dailey, Matthew N.
dc.contributor.author Mohsin, Mazhar
dc.contributor.other Guha, Sumanta
dc.contributor.other Ekpanyapong, Mongkol
dc.date.accessioned 2016-07-01T03:55:26Z
dc.date.available 2016-07-01T03:55:26Z
dc.date.issued 2016-07
dc.identifier.other AIT
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/825
dc.description.abstract In recent years there has been an increasing number of terrorist attacks and bomb blasts in many public places. Video surveillance systems used in these places currently require monitoring by human operators constantly. This is a very tiring, time consuming, and costly task, requiring many people. Video surveillance systems are ineffective if there is a lack of good monitoring by the personnel employed to monitor them. Even if highly qualified and talented people are recruited for the monitoring of these video surveillance systems, it is quite difficult to constantly and attentively maintain attention on a set of cameras. Automated people tracking systems would be helpful in such situation. Automated people tracking systems can monitor people in real time in crowded places. There are many existing people detection and tracking systems for indoor and outdoor scenes. Most of these systems are tested on publicly available data sets but may only be suitable for specific scenarios. In this research, I compare the performance of head and pedestrian detectors used in combination with the state-of-the-art tracker proposed by Milan, Roth, and Schindler (2014). To evaluate the performance of the methods, I use data acquired from the AIT CCTV network. en_US
dc.description.sponsorship University of Turbat en_US
dc.language.iso en_US en_US
dc.publisher AIT en_US
dc.subject People detection, head detection, visual surveillance, evaluation, dataset, head tracking, people tracking, tracking under occlusion. en_US
dc.title People detection and tracking under occlusion en_US
dc.type Research report en_US


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