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dc.contributor.advisorAndrew B. Lippman.en_US
dc.contributor.authorIyengar, Giridharan Ranganathan, 1969-en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Architecture. Program In Media Arts and Sciences.en_US
dc.date.accessioned2011-03-07T15:11:30Z
dc.date.available2011-03-07T15:11:30Z
dc.date.copyright1999en_US
dc.date.issued1999en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/61538
dc.descriptionThesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 1999.en_US
dc.descriptionIncludes bibliographical references (p. 135-139).en_US
dc.description.abstractIn 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.en_US
dc.description.statementofresponsibilityby Giridharan Ranganathan Iyengar.en_US
dc.format.extent140 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectArchitecture. Program In Media Arts and Sciences.en_US
dc.titleCharacterization of unstructured videoen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)
dc.identifier.oclc43923714en_US


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