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
- 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
py_camglyph.py running off an AXIS CCTV Camera video stream.
- CMake
- C++ Compiler (clang or gcc with C++11 support)
- OpenCV 3.0
- OpenCL-enabled GPU
- Python 2.7
- Numpy