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  Published Paper Details:

  Paper Title

Surveillance-based Suspicious Activity Detection: Techniques, Application and Challenges

  Authors

  Nandini Fal Dessai,  Prof. Shruti Pednekar

  Keywords

CNN, LRCN, Suspicious Activity, Non-Suspicious Activity.

  Abstract


Suspicious activity identification from surveillance video is an effective research area of image processing and computer vision. Detecting suspicious activities is significant for maintaining the security of organizations and communities. Surveillance cameras are mostly used in public areas to monitor and secure safety. It is difficult to observe public places continuously, so hence intelligent video surveillance is needed that can detect human activity in real-time and classify them as non-suspicious & suspicious activities. To solve these problems, we will create a Long-term recurrent convolutional network (LRCN) system to record the CCTV footage and to detect suspicious & non-suspicious activities. The system is also used to generate an alarm that will inform the user if any suspicious activities are detected.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2305545

  Paper ID - 236596

  Page Number(s) - e313-e316

  Pubished in - Volume 11 | Issue 5 | May 2023

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.34290

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Nandini Fal Dessai,  Prof. Shruti Pednekar,   "Surveillance-based Suspicious Activity Detection: Techniques, Application and Challenges", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 5, pp.e313-e316, May 2023, Available at :http://www.ijcrt.org/papers/IJCRT2305545.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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