Robotics surveillance project

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dc.contributor.authorkhadase, Rahul
dc.contributor.authorMatiur, Rehman (12ET80)
dc.contributor.authorSayed, Saleem (12ET84)
dc.contributor.authorQureshi, Mehtab Alam (11ET59)
dc.date.accessioned2015-12-14T05:18:23Z
dc.date.available2015-12-14T05:18:23Z
dc.date.issued2015-05
dc.description.abstractABSTRACT: Object tracking is a challenging task in spite of all sophisticated methods that have been de-veloped. The major challenge is to keep track of the object of a particular choice. In this work, a new video moving object-tracking method is proposed. The segmentation of the video is done by contextual clustering. Clustering is an important method in data analysis because of its ability to ‘discover’ the inherent features in the data. The fundamental concept in clustering techniques is to group a given set of objects into subsets according to properties associated with each object, so that the members in each individual subset share some similar properly defined features. A multitarget human tracking is attempted.en_US
dc.identifier.urihttp://www.aiktcdspace.org:8080/jspui/handle/123456789/1375
dc.language.isoen_USen_US
dc.publisherAIKTCen_US
dc.subjectProject Report - EXTCen_US
dc.titleRobotics surveillance projecten_US
dc.typeProject Reporten_US
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