Files in this item



application/pdf3314861.pdf (2MB)Restricted to U of Illinois
(no description provided)PDF


Title:Discovering Audio-Visual Associations in Narrated Videos of Human Activities
Author(s):Oezer, Tuna
Doctoral Committee Chair(s):Sylvian Ray
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Computer Science
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.
Issue Date:2008
Description:143 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008.
Other Identifier(s):(MiAaPQ)AAI3314861
Date Available in IDEALS:2015-09-25
Date Deposited:2008

This item appears in the following Collection(s)

Item Statistics