Document Type
Dissertation
Degree
Doctor of Philosophy (PhD)
Major/Program
Computer Science
First Advisor's Name
Shu-Ching Chen
First Advisor's Committee Title
Committee Chair
Second Advisor's Name
Keqi Zhang
Third Advisor's Name
Mei-Ling Shvu
Fourth Advisor's Name
Nagarajan Prabakar
Fifth Advisor's Name
Jainendra K. Navlakha
Sixth Advisor's Name
Yi Deng
Date of Defense
3-23-2007
Abstract
With the proliferation of multimedia data and ever-growing requests for multimedia applications, there is an increasing need for efficient and effective indexing, storage and retrieval of multimedia data, such as graphics, images, animation, video, audio and text. Due to the special characteristics of the multimedia data, the Multimedia Database management Systems (MMDBMSs) have emerged and attracted great research attention in recent years. Though much research effort has been devoted to this area, it is still far from maturity and there exist many open issues. In this dissertation, with the focus of addressing three of the essential challenges in developing the MMDBMS, namely, semantic gap, perception subjectivity and data organization, a systematic and integrated framework is proposed with video database and image database serving as the testbed. In particular, the framework addresses these challenges separately yet coherently from three main aspects of a MMDBMS: multimedia data representation, indexing and retrieval. In terms of multimedia data representation, the key to address the semantic gap issue is to intelligently and automatically model the mid-level representation and/or semi-semantic descriptors besides the extraction of the low-level media features. The data organization challenge is mainly addressed by the aspect of media indexing where various levels of indexing are required to support the diverse query requirements. In particular, the focus of this study is to facilitate the high-level video indexing by proposing a multimodal event mining framework associated with temporal knowledge discovery approaches. With respect to the perception subjectivity issue, advanced techniques are proposed to support users’ interaction and to effectively model users’ perception from the feedback at both the image-level and object-level.
Identifier
FI14060171
Recommended Citation
Chen, Min, "Knowledge assisted data management and retrieval in multimedia database sistems" (2007). FIU Electronic Theses and Dissertations. 2139.
https://digitalcommons.fiu.edu/etd/2139
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