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Particle Filtering for People Tracking in Surveillance Video

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dc.contributor.advisor Dailey, Dr. Matthew N.
dc.contributor.author Alexandre, Jayet-Laraffe
dc.contributor.other Guha, Prof. Sumanta
dc.contributor.other Ekpanyapong, Dr. Mongkol
dc.date.accessioned 2017-07-04T08:19:30Z
dc.date.available 2017-07-04T08:19:30Z
dc.date.issued 2017-05
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/857
dc.description.abstract Surveillance and security are two main notions in public debates all around the world. Due to both terrorist attacks and crime, people want more surveillance but want it to be less intrusive. That is why video surveillance is currently a key technology. However, monitoring everyone is impossible, not only because of hardware costs, but also because of human resources. Automating video surveillance could be the best way to improve the power and the efficiency of surveillance. Particle filtering is one of the most powerful ways to track objects in video. I define and explore the possibility of adapting particle filtering to the video surveillance problem. However, I will go further by tackle the issue of the use of the Histogram of Oriented Gradients (HOG) as an appearance model for the particle filtering. This study deals with the huge possibilities offered by the HOG but also with the problem created by this use, especially the computational resources needed. That why I will develop my own methodology to compute multiple HOG in the particle filtering context. This method is based on a pre-multiscalecomputation of the HOG. And finally all these methods will be combined not only for a monitoring purpose, but especially for an economic goal, which is the building of statistic about the customers. That is why the last step of this study will be the 3D computation of the location of the customers to create a heat map of the shop. en_US
dc.description.sponsorship Telecom SudParis en_US
dc.publisher AIT en_US
dc.title Particle Filtering for People Tracking in Surveillance Video en_US
dc.type Thesis en_US

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