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Knowledge assisted data management a...

Chen, Min.

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Knowledge assisted data management and retrieval in multimedia database systems.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Knowledge assisted data management and retrieval in multimedia database systems./
作者:	Chen, Min.
面頁冊數:	160 p.
附註:	Adviser: Shu-Ching Chen.
Contained By:	Dissertation Abstracts International68-06B.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3268643
ISBN:	9780549083351

Knowledge assisted data management and retrieval in multimedia database systems.
Chen, Min.

Knowledge assisted data management and retrieval in multimedia database systems. - 160 p.

Adviser: Shu-Ching Chen.

Thesis (Ph.D.)--Florida International University, 2007.

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.

ISBN: 9780549083351Subjects--Topical Terms:

626642
Computer Science.

Knowledge assisted data management and retrieval in multimedia database systems.
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520 $a 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.
520 $a 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.
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