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
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
STARS Citation
Rasheed, Zeeshan, "Video categorization using semantics and semiotics" (2003). Retrospective Theses and Dissertations. 989.
https://stars.library.ucf.edu/rtd/989
Contributor (Linked data)
Shah, Mubarak [VIAF]
Shah, Mubarak [LC]
University of Central Florida. College of Engineering and Computer Science (Q7895235)
University of Central Florida. College of Engineering and Computer Science [VIAF]
University of Central Florida. College of Engineering and Computer Science [LC]