Keywords

Digital video; Image processing -- Digital techniques; Information storage and retrieval systems

Abstract

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.

Graduation Date

2003

Advisor

Shah, Murbarak

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

School of Electrical Engineering and Computer Science

Degree Program

Electrical Engineering and Computer Science

Format

PDF

Pages

120 p.

Language

English

Rights

Written permission granted by copyright holder to the University of Central Florida Libraries to digitize and distribute for nonprofit, educational purposes.

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Identifier

DP0001717

Subjects

Dissertations, Academic -- Engineering; Engineering -- Dissertations, Academic

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