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Modular Tracking Framework: A Unified Approach to Registration based Tracking

  • Author / Creator
    Singh, Abhineet K
  • This thesis presents a new way to conceptualize and study image registration based visual trackers by decomposing them into three constituent sub modules - search method, appearance model and state space model. It shows how this approach can be used to break down existing trackers and thus unify the myriad of contributions that have been made in this domain in over three decades of its existence. Further, a modular framework for registration based tracking is introduced to provide practical validity to this formulation. It provides highly efficient C++ implementations for a large subset of trackers introduced in literature to date and is designed to be easily extensible with additional methods. It follows this decomposition closely through extensive use of generic programming to provide a convenient interface to plug in a new method for any sub module and test it against all possible combinations of methods for the others. This can not only help to evaluate the new method in a more comprehensive manner but also make it immediately available for deployment in any project that uses the framework. Finally, three existing image similarity measures are adapted for high precision tracking and a new one is introduced to serve as case studies for the proposed approach of analyzing registration based tracking. Experiments are conducted using synthetic data as well as four large publicly available datasets with over 100000 frames in all to ensure the statistical validity of the results.

  • Subjects / Keywords
  • Graduation date
    Fall 2017
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3FJ29S7K
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.