Browsing by Author "Qureshi, Mehtab Alam (11ET59)"

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    Robotics surveillance project
    (AIKTC, 2015-05) khadase, Rahul; Matiur, Rehman (12ET80); Sayed, Saleem (12ET84); Qureshi, Mehtab Alam (11ET59)
    ABSTRACT: 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.