株式会社極東書店トップ商品一覧Video Object Extraction and Representation: Theory and Applications. Softcover reprint of the original 1st ed. 2002

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Video Object Extraction and Representation: Theory and Applications. Softcover reprint of the original 1st ed. 2002

Video Object Extraction and Representation: Theory and Applications. Softcover reprint of the original 1st ed. 2002

・ISBN 978-1-4757-8384-1 paper EUR 99.99

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お気に入り
著者・編者I-Jong Lin / Kung, S.Y.,
シリーズ (The Springer International Series in Engineering and Computer Science)
出版社 (Springer-Verlag New York Inc., US)
出版年月2013
ページ数177 pp.
言語ENG
ニュース番号<A05-27856>

解説

"If you have built castles in the air, your work need not be lost; that is where they should be. Now put the foundations under them. " - Henry David Thoreau, Walden Although engineering is a study entrenched firmly in belief of pr- matism, I have always believed its impact need not be limited to pr- matism. Pragmatism is not the boundaries that define engineering, just the (sometimes unforgiving) rules by which we sight our goals. This book studies two major problems of content-based video proce- ing for a media-based technology: Video Object Plane (VOP) Extr- tion and Representation, in support of the MPEG-4 and MPEG-7 video standards, respectively. After reviewing relevant image and video p- cessing techniques, we introduce the concept of Voronoi Ordered Spaces for both VOP extraction and representation to integrate shape infor- tion into low-level optimization algorithms and to derive robust shape descriptors, respectively. We implement a video object segmentation system with a novel surface optimization scheme that integrates Voronoi Ordered Spaces with existing techniques to balance visual information against predictions of models of a priori information. With these VOPs, we have explicit forms of video objects that give users the ability to - dress and manipulate video content. We outline a general methodology of robust data representation and comparison through the concept of complex partitioning mapped onto Directed Acyclic Graphs (DAGs).