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RealTimeObjectDetection 🎥

Created an application utilising an in-built webcam or external camera to detect humans through facial recognition and other objects, providing an output to the frame contents.

Features:

  • Security Camera with built-in activation timer for human detection.
  • Facial Recognition to detect whether the human is recognised or new.
  • Saves videos with a timestamp.
  • Option for manual photos taken.
  • Use of webcam or external webcam.

Challenges:

  • The HOG algorithm would often have difficult in correctly identifying the person if they are too close or too far from the camera.
  • Some cameras work better than others, and therefore has varying effects on how well the HOG algorithm performs.
  • The HOG algorithm also detects images of people on photos or paintings which can affect the detection of when a real person walks into the frame. This is shown below:

image

  • The practibility of this program is limited unless you are using an extendable webcam or a remote webcam.

Upcoming changes

[] Creating a GUI for option choices.

Languages and tools used:

Created with Python, OpenCV, and numpy.

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A security camera for detecting people entering the frame, starting a timer and adding an identifier.

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