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Introduction

CMT (Consensus-based Matching and Tracking of Keypoints for Object Tracking) is a novel keypoint-based method for long-term model-free object tracking in a combined matching-and-tracking framework. Details can be found on the project page and in our publication. The Python implementation in this repository is platform-independent and runs on Linux, Windows and OS X.

#License CMT is freely available under the 3-clause BSD license, meaning that you can basically do with the code whatever you want. If you use our algorithm in scientific work, please cite our publication

@inproceedings{Nebehay2014WACV,
    author = {Nebehay, Georg and Pflugfelder, Roman},
    booktitle = {Winter Conference on Applications of Computer Vision},
    month = mar,
    publisher = {IEEE},
    title = {Consensus-based Matching and Tracking of Keypoints for Object Tracking},
    year = {2014}
}

Dependencies

  • Python
  • OpenCV-Python (>= 2.4)
  • NumPy
  • SciPy
  • optional: ipdb (for debugging the code)

Note for Windows users: if you are unable to read video files, please follow this suggestion: http://stackoverflow.com/questions/11699298/opencv-2-4-videocapture-not-working-on-windows

Usage

usage: python ObjectTracker.py

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  • Python 100.0%