Achievements and challenges in recognizing and reconstructing civil infrastructure

  • Authors:

  • Ioannis Brilakis;Fei Dai;Stefania-Christina Radopoulou

  • Affiliations:

  • School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA;School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA;School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA

  • Venue:
  • Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
  • Year:
  • 2011

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Abstract

The US National Academy of Engineering recently identified restoring and improving urban infrastructure as one of the grand challenges of engineering. Part of this challenge stems from the lack of viable methods to map/label existing infrastructure. For computer vision, this challenge becomes "How can we automate the process of extracting geometric, object oriented models of infrastructure from visual data?" Object recognition and reconstruction methods have been successfully devised and/or adapted to answer this question for small or linear objects (e.g. columns). However, many infrastructure objects are large and/or planar without significant and distinctive features, such as walls, floor slabs, and bridge decks. How can we recognize and reconstruct them in a 3D model? In this paper, strategies for infrastructure object recognition and reconstruction are presented, to set the stage for posing the question above and discuss future research in featureless, large/planar object recognition and modeling.