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dc.contributor.authorCHOUDHURY, SUBRADEB-
dc.date.accessioned2018-08-21T12:28:27Z-
dc.date.available2018-08-21T12:28:27Z-
dc.date.issued2013-07-
dc.identifier.urihttp://dspace.dtu.ac.in:8080/jspui/handle/repository/16157-
dc.description.abstractVideo Surveillance has received tremendous attention in the present scenario. It has a wide range of applications like it can be used in Border areas of a country or in market areas as well as in the restricted areas for monitoring objects. Human Detection is a field of Video Surveillance where monitoring of humans take place i.e. the human is detected first and its trajectory is estimated for the purpose of monitoring. In this project, a robust human detection method is proposed. The Human Detection System consists of 2 stages. First stage involves Image Pre-processing where the Motion region is extracted and Image Segmentation is applied to this motion region. The second stage classifies the segmented image as a human or a non-human based on Aspect Ratio of Human. So, we can say that the Motion region is incorporated with the Aspect Ratio feature to propose a Robust Human Detection Method. A Dataset is made where the background colour matches with the Human Skin Colour. In this situation it is very difficult to track the human. We propose a system where we can track human under such conditions. The system is tested in PETs Database also and an overall Detection Rate of 85% is reported. However, the Detection rate gets reduced drastically when the human is occluded in the scene.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesTD-1205;-
dc.subjectFRAME DIFFERENCINGen_US
dc.subjectASPECT RATIOen_US
dc.subjectHUMAN DETECTIONen_US
dc.subjectHOGen_US
dc.titleROBUST HUMAN DETECTION FOR SURVEILLANCEen_US
dc.typeThesisen_US
Appears in Collections:M.E./M.Tech. Electronics & Communication Engineering

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