Deep learning is the segment of artificial intelligence which is involved with imitating the learning approach that human beings utilize to get some different types of knowledge. Analyzing videos, a part of deep learning is one of the most basic problems of computer vision and multi-media content analysis for at least 20 years. The job is very challenging as the video contains a lot of information with large differences and difficulties. Human supervision is still required in all surveillance systems. New advancement in computer vision which are observed as an important trend in video surveillance leads to dramatic efficiency gains. We propose a CCTV based theft detection along with tracking of thieves. We use image processing to detect theft and motion of thieves in CCTV footage, without the use of sensors. This system concentrates on object detection. The security personnel can be notified about the suspicious individual committing burglary using Real-time analysis of the movement of any human from CCTV footage and thus gives a chance to avert the same.


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    Titel :

    AI Based Automatic Robbery/Theft Detection using Smart Surveillance in Banks


    Beteiligte:
    Kakadiya, Rutvik (Autor:in) / Lemos, Reuel (Autor:in) / Mangalan, Sebin (Autor:in) / Pillai, Meghna (Autor:in) / Nikam, Sneha (Autor:in)


    Erscheinungsdatum :

    2019-06-01


    Format / Umfang :

    3125752 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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