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Master thesis project, in fulfilment of MSc Technical Cybernetics, NTNU. Glyph tracking CCTV camera.

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thesis-master

Implementation for master thesis due 17th of December 2015, fulfilment of MSc in Technical Cybernetics at NTNU.

Mainly developed on OS X 10.10.5, primary execution platform is Linux (Ubuntu 12.04).

Compiled application names:

  • APP_CCTV: Primary effort for following glyph using multiple camera sources and GPU-acceleration
  • APP_BLOBTEST: Used to find proof of concept detection of pipes and casings parameters for SimpleBlobDetector
  • APP_TIMER: A visual timer used for showing latency from camera capture
  • APP_CVEXAMPLE: Used to quickly compile example code

Primary effort

  • Implement glyph tracking in C++ and compare to Python implementation
  • Analyze datasets from outdoor to find failmodes
  • Create proof-of-concept detection of pipes and casings in fingerboards

Screenshot

py_camglyph.py running off an AXIS CCTV Camera video stream. ScreenShot

Dependencies for primary project (non-exhaustive)

  • CMake
  • C++ Compiler (clang or gcc with C++11 support)
  • OpenCV 3.0
  • OpenCL-enabled GPU

Other dependencies (non-exhaustive)

  • Python 2.7
  • Numpy

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Master thesis project, in fulfilment of MSc Technical Cybernetics, NTNU. Glyph tracking CCTV camera.

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