Description

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.

Table of 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.

Big Visual Data Analysis: Scene Classification and Geometric Labeling

    Product form

    A Paperback / softback by Chen Chen, Yuzhuo Ren, C.-C. Jay Kuo

    £999.99

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      Book details

      Publisher Springer Verlag, Singapore
      Published 3 March 2016
      ISBN-13 9789811006296
      978-9811006296
      ISBN-10 9811006296
      Also in:
      Computing Computer vision Digital signal processing (DSP) Technology, Engineering & Agriculture Electronics engineering

      Description

      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.

      Table of 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.

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