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Titlebook: State-of-the-Art in Content-Based Image and Video Retrieval; Remco C. Veltkamp,Hans Burkhardt,Hans-Peter Kriege Book 2001 Springer Science

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书目名称State-of-the-Art in Content-Based Image and Video Retrieval
编辑Remco C. Veltkamp,Hans Burkhardt,Hans-Peter Kriege
视频video
丛书名称Computational Imaging and Vision
图书封面Titlebook: State-of-the-Art in Content-Based Image and Video Retrieval;  Remco C. Veltkamp,Hans Burkhardt,Hans-Peter Kriege Book 2001 Springer Science
描述Images and video play a crucial role in visual informationsystems and multimedia. There is an extraordinary number ofapplications of such systems in entertainment, business, art,engineering, and science. Such applications often involved large imageand video collections, and therefore, searching for images and videoin large collections is becoming an important operation. Because ofthe size of such databases, efficiency is crucial. We strongly believethat image and video retrieval need an integrated approach from fieldssuch as image processing, shape processing, perception, databaseindexing, visualization, and querying, etc. .This book contains a selection of results that was presented at theDagstuhl Seminar on Content-Based Image and Video Retrieval, inDecember 1999. The purpose of this seminar was to bring togetherpeople from the various fields, in order to promote informationexchange and interaction among researchers who are interested invarious aspects of accessing the content of image and video data. Thebook provides an overview of the state of the art in content-basedimage and video retrieval. The topics covered by the chapters areintegrated system aspects, as well as technique
出版日期Book 2001
关键词computer vision; database; graphics; image databases; image processing; information; information retrieval
版次1
doihttps://doi.org/10.1007/978-94-015-9664-0
isbn_softcover978-90-481-5863-8
isbn_ebook978-94-015-9664-0Series ISSN 1381-6446
issn_series 1381-6446
copyrightSpringer Science+Business Media Dordrecht 2001
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State-of-the-Art in Content-Based Image and Video Retrieval978-94-015-9664-0Series ISSN 1381-6446
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Computational Imaging and Visionhttp://image.papertrans.cn/s/image/876154.jpg
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https://doi.org/10.1007/978-94-015-9664-0computer vision; database; graphics; image databases; image processing; information; information retrieval
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Distribution-Free Statistics for Segmentation,t) density that is still compatible with the data. Compatibility is given a precise meaning in terms of distribution-free statistics based on the empirical distribution function. We apply this algorithm to image-segmentation based on data-driven 1-dimensional colour-spaces.
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New Descriptors for Image and Video Indexing,are an extension of the descriptors proposed by Florack et al. and Schmid to the case of color images. They are suited for object recognition in still images. The second ones describe the global level of motion activity in an image sequence, and are a good complement to the traditional color and texture descriptors.
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