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.
Presents a comprehensive big visual data analysis methodology that helps readers understand the topic quickly and fully Includes abundant insightful data analysis results and comparisons that can be used for other related computer-vision tasks such as scene analysis and image comprehension Provides source codes of data analysis applications
(indoor/outdoor classification and vanishing point detection) so that readers
can test the algorithms and develop more advanced applications Written
by leading experts in the field Includes supplementary material: sn.pub/extras
Chen Chen
Big Visual Data Analysis Scene Understanding Indoor/Outdoor Classification Outdoor Scene Classification Outdoor Scene Geometric Labeling