A dynamic key frames approach to object tracking
Name
417813636-MIT.pdf
Description
Full printable version
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594.06 KB
Format
Adobe PDF
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Author(s)
Wilkens, Christopher A
Advisor(s)
David Demirdjian.
Date Issued
2008
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, I present a dynamic key frames algorithm for state estimation from observations. The algorithm uses KL-divergence as a metric to identify the frames that contribute the most information to estimation of the system's current state. The algorithm is first presented in a numerical optimization framework and then developed as an extension to the Condensation algorithm. Finally, I present results from a Matlab simulation of the algorithm.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 95-96).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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