Discovering Audio-Visual Associations in Narrated Videos of Human Activities
Oezer, Tuna
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Permalink
https://hdl.handle.net/2142/81814
Description
Title
Discovering Audio-Visual Associations in Narrated Videos of Human Activities
Author(s)
Oezer, Tuna
Issue Date
2008
Doctoral Committee Chair(s)
Sylvian Ray
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
The experimental results show that the algorithm presented in this dissertation successfully discovers the correct associations between video scenes and audio utterances in an unsupervised way despite the imperfect correlation between the video and audio. The algorithm outperforms standard supervised learning algorithms. Among other things, this research shows that the performance of the algorithm depends mainly on the strength of the correlation between video and audio, the length of the narration associated with each video scene and the total number of words in the language.
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