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SUCCESS STORIES

VIDEO SURVEILLANCE

Problem/Challenges

Identify suspicious behavior of individuals at ATMs, using real-time CCTV footage. Model needed to run on a Raspberry Pi.

Innovation

  • 1.Developed a DL model that can identify the location of people in a video.
  • 2.Developed a DL model to identify facial key points of a people present within the ATM.
  • 3.Developed light weight models, so that the solution can be implemented on edge device like Raspberry Pi.

Approach

  • 1.Designed a deep learning model to analyze video footage and accurately determine the location of a person within each frame.
  • 2.Designed a deep learning model to analyze people‚Äôs face in order to identify key facial points on the face.
  • 3.Designed a pipeline to use the features identified by both deep learning models to determine fraudulence.
  • 4.Ensured that the models were lightweight so that the models could run on a edge device such as Raspberry Pi.

Result

98% accuracy in identifying people and 97% accuracy in identifying facial key points.