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Big visual data analysisscene classi...

Chen, Chen.

Big visual data analysisscene classification and geometric labeling /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Big visual data analysisby Chen Chen, Yuzhuo Ren, C.-C. Jay Kuo.
Reminder of title:	scene classification and geometric labeling /
Author:	Chen, Chen.
other author:	Ren, Yuzhuo.
Published:	Singapore :Springer Singapore :2016.
Description:	x, 122 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Computer vision.
Online resource:	http://dx.doi.org/10.1007/978-981-10-0631-9
ISBN:	9789811006319$q(electronic bk.)

Big visual data analysisscene 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$q(electronic bk.)

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

200113
Computer vision.

LC Class. No.: TA1634

Dewey Class. No.: 006.37

Big visual data analysisscene classification and geometric labeling /
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