2026-09-18T23:21:01Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/615382022-01-13T07:55:04Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Andrew B. Lippman.
Iyengar, Giridharan Ranganathan, 1969-
Massachusetts Institute of Technology. Dept. of Architecture. Program In Media Arts and Sciences.
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
2011-03-07T15:11:30Z
2011-03-07T15:11:30Z
1999
1999
http://hdl.handle.net/1721.1/61538
43923714
Thesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 1999.
Includes bibliographical references (p. 135-139).
In this work, we examine video retrieval from a synthesis perspective in co-operation with the more common analysis perspective. Specifically, we target our algorithms for one particular domain- unstructured video material. The goal is to make this unstructured video available for manipulation in interesting ways. I.e, take video that may have been shot with no specific intent and use it in different settings. For example, we build a set of interfaces that will enable taking a collection of home videos and making Christmas cards, Refrigerator magnets, family dramas etc out of them. The work is divided into three parts. First, we study features and models for characterization of video. Examples are VideoBook with its extensions and Hidden Markov Models for video analysis. Secondly, we examine clustering as an approach for characterization of unstructured video. Clustering alleviates some of the common problems with "query-by- example" and presents groupings that rely on the user's abilities to make relevant connections. The clustering techniques we employ operate in the probability density space. One of our goals is to employ these techniques with sophisticated models such as Bayesian Networks and HMMs, which give similar descriptions. The clustering techniques we employ are shown to be optimal in an information theoretic and Gibbs Free Energy sense. Finally, we present a set of interfaces that use these features and groupings to enable browsing and editing of unstructured video content.
by Giridharan Ranganathan Iyengar.
Ph.D.
140 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Architecture. Program In Media Arts and Sciences.
Characterization of unstructured video
Thesis
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