• Chen ChenEmail author
  • Yuzhuo Ren
  • C.-C. Jay Kuo
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)


Large-scale visual data understanding is a long-standing popular problem in the computer vision society. When more visual data become available, problems become more challenging to traditional approaches. In this chapter, we will briefly review three important research problems, indoor/outdoor classification, outdoor scene categorization and geometric labeling. In addition, we will provide an overview of the book and its perspective benefits to the readers.


Big visual data Indoor/Outdoor classification Outdoor scene classification Geometric labeling Decision fusion Structured machine learning system Contour-guided color palette Semantic segmentation Context-aware labeling Global attributes 


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Copyright information

© The Author(s) 2016

Authors and Affiliations

  1. 1.Department of Electrical EngineeringUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.University of Southern CaliforniaLos AngelesUSA

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