Big Visual Data Analysis Scene Classification and Geometric Labeling
Aus der Reihe
SpringerBriefs in Electrical and Computer Engineering
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Sprache:Englisch
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Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
03.03.2016
Abbildungen
X, 94 illus., 12 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen
Verlag
Springer SingaporeSeitenzahl
122
Maße (L/B/H)
23,5/15,5/0,8 cm
Gewicht
213 g
Auflage
1st edition 2016
Sprache
Englisch
ISBN
978-981-10-0629-6
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.
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.
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