| dc.contributor.advisor | David Demirdjian. | en_US |
| dc.contributor.author | Wilkens, Christopher A | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2009-08-25T17:59:38Z | |
| dc.date.available | 2009-08-25T17:59:38Z | |
| dc.date.copyright | 2008 | en_US |
| dc.date.issued | 2008 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1721.1/46366 | |
| dc.description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. | en_US |
| dc.description | This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. | en_US |
| dc.description | Includes bibliographical references (p. 95-96). | en_US |
| dc.description.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. | en_US |
| dc.description.statementofresponsibility | by Christopher A. Wilkens. | en_US |
| dc.format.extent | 96 p. | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
reproduction or distribution in any format is prohibited without written
permission. See provided URL for inquiries about permission. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Electrical Engineering and Computer Science. | en_US |
| dc.title | A dynamic key frames approach to object tracking | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | M.Eng. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| dc.identifier.oclc | 417813636 | en_US |
