Cover image for Big Visual Data Analysis Scene Classification and Geometric Labeling
Big Visual Data Analysis Scene Classification and Geometric Labeling
Title:
Big Visual Data Analysis Scene Classification and Geometric Labeling
Author:
Chen, Chen. author.
ISBN:
9789811006319
Personal Author:
Edition:
1st ed. 2016.
Physical Description:
X, 122 p. 94 illus., 12 illus. in color. online resource.
Series:
SpringerBriefs in Signal Processing,
Contents:
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.
Abstract:
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.
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