• Login
    View Item 
    •   DBS eSource Home
    • Masters Dissertations
    • Information & Communications Technology
    • View Item
    •   DBS eSource Home
    • Masters Dissertations
    • Information & Communications Technology
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Real time social distancing violation detection using SVM classifier and deep neural network learning techniques

    View/Open
    msc_chaudhary_a_2020.pdf (1.187Mb)
    Author
    Chaudhary, Aatiya
    Date
    2020
    Degree
    MSc in Data Analytics
    URI
    https://esource.dbs.ie/handle/10788/4243
    Publisher
    Dublin Business School
    Rights holder
    http://esource.dbs.ie/copyright
    Rights
    Items in eSource are protected by copyright. Previously published items are made available in accordance with the copyright policy of the publisher/copyright holder.
    Metadata
    Show full item record
    Abstract
    Whenever world is hit by any pandemic, it creates immediate global health crises due its deadly spread. Social Distancing is the key measure to control the spread of any pandemic in absence of immediate pharmaceutical inventions. Motivated by current world situation due to COVID-19, the research proposes real time detection framework for monitoring social distancing in public areas for current and any future situations. The detection framework is developed using Support Vector Classifier (SVM) with Histogram of Gradient (HOG) and pre-trained neural network models. The result of two models is compared in terms of dimensions of detection box area. The pre-trained neural network model trained using transfer learning is observed to provide better detection results. It is used to feed on real time video to compute the pairwise centroid distance of the features in three dimensional spaces using tensor flow package. The social distancing violation term is proposed to run the experimental analysis and displays the top view of the detection to give real-time view for security surveillance representing the colour change depicting alerts.
    Collections
    • Information & Communications Technology

    Browse

    All of DBS eSourceCommunities & CollectionsBy Issue DateAuthorsSupervisorTitlesSubjectsThis CollectionBy Issue DateAuthorsSupervisorTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    DSpace software copyright © 2002-2023  DuraSpace
    Contact Us | Send Feedback
    DSpace Express is a service operated by 
    Atmire NV