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Content-based management of image da...

Kleban, James Theodore.

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Content-based management of image databases in the Internet Age.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Content-based management of image databases in the Internet Age./
作者:	Kleban, James Theodore.
面頁冊數:	271 p.
附註:	Source: Dissertation Abstracts International, Volume: 72-01, Section: B, page: 0432.
Contained By:	Dissertation Abstracts International72-01B.
標題:	Information Technology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3427856
ISBN:	9781124330495

Content-based management of image databases in the Internet Age.
Kleban, James Theodore.

Content-based management of image databases in the Internet Age. - 271 p.

Source: Dissertation Abstracts International, Volume: 72-01, Section: B, page: 0432.

Thesis (D.Eng.)--University of California, Santa Barbara, 2010.

The Internet Age has seen the emergence of richly annotated image data collections numbering in the billions of items. This work makes contributions in three primary areas which aid the management of this data: image representation, efficient retrieval, and annotation based on content and metadata.

ISBN: 9781124330495Subjects--Topical Terms:

1030799
Information Technology.

Content-based management of image databases in the Internet Age.
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500 $a Source: Dissertation Abstracts International, Volume: 72-01, Section: B, page: 0432.
500 $a Adviser: Bangalore S. Manjunath.
502 $a Thesis (D.Eng.)--University of California, Santa Barbara, 2010.
520 $a The Internet Age has seen the emergence of richly annotated image data collections numbering in the billions of items. This work makes contributions in three primary areas which aid the management of this data: image representation, efficient retrieval, and annotation based on content and metadata.
520 $a The contributions are as follows. First, Spatial Mining Pyramid (SPM) hierarchically mines configurations of discriminative local features in an extension of the bag-of-features representation. SPM can also be incorporated into a boosting framework for building classification models. Second, Compressed Vector Ordering (CVO) provides an improved indexing scheme for exact k-nearest neighbor image retrieval. CVO uses distance bounds from approximation files to order clustered retrieval in a way which requires fewer random and sequential disk accesses than other state-of-the-art approaches. Third, SpiritTagger employs a Bayesian framework for automatically annotating georeferenced photos by simultaneously considering low level visual features and geographic tag frequency. Experiments show annotation performance improves in densely photographed areas and by appropriately filtering the tags. A real-time web demo of the annotation system provides tag suggestions on previously unseen photographs by mining over 1.4 million images.
520 $a The trend towards increasingly larger collections of data online continues. With effective organization and modeling the scale of user contributed data can empower incredible new applications. This thesis provides flexible techniques for such applications via content-based mining and retrieval of image data.
590 $a School code: 0035.
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