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  Published Paper Details:

  Paper Title

REAL TIME CRIME DETECTION BY CAPTIONING VIDEO SURVEILLANCE USING DEEP LEARNING

  Authors

  Sapna Patwa,  Nagesh Nayak,  Shlesha Odhekar,  Sukanya Roychowdhury

  Keywords

Crime Detection, Video captioning, CCTV, Real time

  Abstract


CCTVs are commonly used for surveillance almost everywhere in the world. Despite that, there are a large number of crimes happening due to the lack of a proper system to detect crimes or such types of behavior and control rates of illegal activities. Our project not only deals with detecting crimes from the video data received in real-time from CCTVs but also solves problems beyond this. Storing video data is a huge problem, and also it is less secure. Our application solves this problem by eliminating the need to store the videos themselves. Instead, a better solution is to store only the accurate captions of the events happening in the video along with the respective timestamp. Crimes are detected based on the captions generated by detecting certain crime-related keywords like a knife, thief, fire, assault, etc. we store these captions in text files along with the timestamp so we can even search for a particular event in the log. It is also more secure than storing CCTV captured videos as we will actually, be storing a text file and it can be encrypted using good encryption algorithms. Video, photos, and notifications of crime in real-time time is sent to a human supervisor to act in a responsible manner

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2207445

  Paper ID - 217742

  Page Number(s) - d367-d376

  Pubished in - Volume 10 | Issue 7 | July 2022

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  Sapna Patwa,  Nagesh Nayak,  Shlesha Odhekar,  Sukanya Roychowdhury,   "REAL TIME CRIME DETECTION BY CAPTIONING VIDEO SURVEILLANCE USING DEEP LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 7, pp.d367-d376, July 2022, Available at :http://www.ijcrt.org/papers/IJCRT2207445.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: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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