Human Activity Recognition using Deep Learning | Violence Detection using Machine Learning

Abnormal Activity Detection using Deep Learning

Suspicious Activity Detection in videos is a fascinating area of computer vision that aims to automatically identify unusual or anomalous events from video footage. By leveraging machine learning algorithms and computer vision techniques, it becomes possible to develop systems that can detect abnormal activities, such as fighting, robbery, abuse, or suspicious behavior, in real-time.

In security systems anomaly activity detection is one among them. Surveillance cameras have been setup widely for video analysis due to increasing demand for security. Video footages are captured and stored in memory devices. Several places or organization have installed CCTV Cameras for continuous monitoring for surveillance. It is impossible to manually monitor all activities and predict their behavior.

Detecting real-world problem such as robbery, shoplifting, break-in and other critical events is crucial so that we have to create a deep learning based model to reduce time and manual work.

Suspicious Activity Detection from CCTV Footage

Software Requirements :-

  • Coding Language : Python
  • Implementation: Software Framework.
  • Operating system : Windows 10 / 11.
  • Graphical User Interface : Tkinter

Hardware Requirement:-

  • Input Devices : Keyboard, Mouse.
  • System : Pentium i3 Processor.
  • Hard Disk : 500 GB.
  • RAM : 4 GB.

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