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Global-Attributes Assisted Outdoor Scene Geometric Labeling

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

Abstract

An approach that extracts global attributes from outdoor images to facilitate geometric layout labeling is investigated in this work. The proposed Global-attributes Assisted Labeling (GAL) system exploits both local features and global attributes. First, by following a classical framework, we use local features to provide initial labels for all superpixels. Then, we develop a set of techniques to extract global attributes from 2D outdoor images. They include sky lines, ground lines, vanishing lines, etc. Finally, we propose the GAL system that uses global attributes to correct local features-based initial labels so as to offer a more robust labeling result. The performance of the proposed GAL system is demonstrated and benchmarked with several state-of-the- art algorithms against a popular outdoor scene layout dataset.

Keywords

Geometric label Outdoor scene understanding Image segmentation Segmental labeling Coarse semantic segmentation 

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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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