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Big visual data analysis[electronic resource] :scene classification and geometric labeling /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.37
書名/作者:	Big visual data analysis : scene classification and geometric labeling // by Chen Chen, Yuzhuo Ren, C.-C. Jay Kuo.
作者:	Chen, Chen.
其他作者:	Ren, Yuzhuo.
出版者:	Singapore : : Springer Singapore :, 2016.
面頁冊數:	x, 122 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Computer vision.
標題:	Image processing - Digital techniques.
標題:	Engineering.
標題:	Signal, Image and Speech Processing.
標題:	Image Processing and Computer Vision.
標題:	Visualization.
ISBN:	9789811006319
ISBN:	9789811006296
內容註:	Introduction -- Scene Understanding Datasets -- Indoor/Outdoor classiﬁcation with Multiple Experts -- Outdoor Scene Classiﬁcation Using Labeled Segments -- Global-Attributes Assisted Outdoor Scene Geometric Labeling -- Conclusion and Future Work.
摘要、提要註:	This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoor scene classification, and outdoor scene layout estimation. It is illustrated with numerous natural and synthetic color images, and extensive statistical analysis is provided to help readers visualize big visual data distribution and the associated problems. Although there has been some research on big visual data analysis, little work has been published on big image data distribution analysis using the modern statistical approach described in this book. By presenting a complete methodology on big visual data analysis with three illustrative scene comprehension problems, it provides a generic framework that can be applied to other big visual data analysis tasks.
電子資源:	http://dx.doi.org/10.1007/978-981-10-0631-9

Big visual data analysis[electronic resource] :scene classification and geometric labeling /
Chen, Chen.

Big visual data analysisscene classification and geometric labeling /[electronic resource] :by Chen Chen, Yuzhuo Ren, C.-C. Jay Kuo. - Singapore :Springer Singapore :2016. - x, 122 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering,2191-8112. - SpringerBriefs in electrical and computer engineering..

Introduction -- Scene Understanding Datasets -- Indoor/Outdoor classiﬁcation with Multiple Experts -- Outdoor Scene Classiﬁcation Using Labeled Segments -- Global-Attributes Assisted Outdoor Scene Geometric Labeling -- Conclusion and Future Work.

This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoor scene classification, and outdoor scene layout estimation. It is illustrated with numerous natural and synthetic color images, and extensive statistical analysis is provided to help readers visualize big visual data distribution and the associated problems. Although there has been some research on big visual data analysis, little work has been published on big image data distribution analysis using the modern statistical approach described in this book. By presenting a complete methodology on big visual data analysis with three illustrative scene comprehension problems, it provides a generic framework that can be applied to other big visual data analysis tasks.

ISBN: 9789811006319

Standard No.: 10.1007/978-981-10-0631-9doiSubjects--Topical Terms:

403529
Computer vision.

LC Class. No.: TA1634

Dewey Class. No.: 006.37

Big visual data analysis[electronic resource] :scene classification and geometric labeling /
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