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Video categorization using semantics and semiotics

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Date Issued:
2003
Abstract/Description:
University of Central Florida College of Engineering Thesis; There is a great need to automatically segment, categorize, and annotate video data, and to develop efficient tools for browsing and searching. We believe that the categorization of videos can be achieved by exploring the concepts and meanings of the videos. This task requires bridging the gap between low-level content and high-level concepts (or semantics). Once a relationship is established between the low-level computable features of the video and its semantics, .the user would be able to navigate through videos through the use of concepts and ideas (for example, a user could extract only those scenes in an action film that actually contain fights) rat her than sequentially browsing the whole video. However, this relationship must follow the norms of human perception and abide by the rules that are most often followed by the creators (directors) of these videos. These rules are called film grammar in video production literature. Like any natural language, this grammar has several dialects, but it has been acknowledged to be universal. Therefore, the knowledge of film grammar can be exploited effectively for the understanding of films. To interpret an idea using the grammar, we need to first understand the symbols, as in natural languages, and second, understand the rules of combination of these symbols to represent concepts. In order to develop algorithms that exploit this film grammar, it is necessary to relate the symbols of the grammar to computable video features.
Title: Video categorization using semantics and semiotics.
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Name(s): Rasheed, Zeeshan, Author
Shah, Mubarak, Committee Chair
Engineering and Computer Science, Degree Grantor
Type of Resource: text
Date Issued: 2003
Publisher: University of Central Florida
Language(s): English
Abstract/Description: University of Central Florida College of Engineering Thesis; There is a great need to automatically segment, categorize, and annotate video data, and to develop efficient tools for browsing and searching. We believe that the categorization of videos can be achieved by exploring the concepts and meanings of the videos. This task requires bridging the gap between low-level content and high-level concepts (or semantics). Once a relationship is established between the low-level computable features of the video and its semantics, .the user would be able to navigate through videos through the use of concepts and ideas (for example, a user could extract only those scenes in an action film that actually contain fights) rat her than sequentially browsing the whole video. However, this relationship must follow the norms of human perception and abide by the rules that are most often followed by the creators (directors) of these videos. These rules are called film grammar in video production literature. Like any natural language, this grammar has several dialects, but it has been acknowledged to be universal. Therefore, the knowledge of film grammar can be exploited effectively for the understanding of films. To interpret an idea using the grammar, we need to first understand the symbols, as in natural languages, and second, understand the rules of combination of these symbols to represent concepts. In order to develop algorithms that exploit this film grammar, it is necessary to relate the symbols of the grammar to computable video features.
Identifier: CFR0001717 (IID), ucf:52920 (fedora)
Note(s): 2003-12-01
Ph.D.
Electrical Engineering and Computer Science
Doctorate
This record was generated from author submitted information.
Electronically reproduced by the University of Central Florida from a book held in the John C. Hitt Library at the University of Central Florida, Orlando.
Subject(s): Digital video
Dissertations
Academic -- Engineering
Engineering -- Dissertations
Academic
Image processing -- Digital techniques
Information storage and retrieval systems
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFR0001717
Restrictions on Access: public
Host Institution: UCF

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