Please refer these papers: [cviu] [iros17] for details on the system design, these: [crv16][wacv17][crv17] for some performance results and this thesis for a comprehensive description. There is also a dedicated website where Doxygen documentation will soon be available along with detailed tutorials and examples. It also provides several datasets formatted to work with MTF. The library is implemented entirely in C++ though interfaces for Python and MATLAB are also provided to aid its use in research applications. A simple interface for ROS is likewise provided for seamless integration with robotics projects. In addition to the registration tracking modules, MTF comes bundled with several state of the art learning and detection based trackers whose C++ implementations are publicly available - DSST, KCF, CMT, TLD, RCT, MIL, Struck, FragTrack, GOTURN and DFT. It can thus be used as a general purpose tracking test bed too.