Quantitative evaluation strategies for urban 3D model generation from remote sensing data

Linh Truong-Hong, Debra F. Laefer

Research output: Contribution to journalArticle

Abstract

Over the last decade, several automatic approaches have been proposed to reconstruct 3D building models from aerial laser scanning (ALS) data. Typically, they have been benchmarked with data sets having densities of less than 25 points/m2. However, these test data sets lack significant geometric points on vertical surfaces. With recent sensor improvements in airborne laser scanners and changes in flight path planning, the quality and density of ALS data have improved significantly. The paper presents quantitative evaluation strategies for building extraction and reconstruction when using dense data sets. The evaluation strategies measure not only the capacity of a method to detect and reconstruct individual buildings but also the quality of the reconstructed building models in terms of shape similarity and positional accuracy.

Original languageEnglish (US)
Pages (from-to)82-91
Number of pages10
JournalComputers and Graphics (Pergamon)
Volume49
DOIs
StatePublished - Jul 28 2015

Keywords

  • Aerial laser scanning
  • Building detection
  • Building reconstruction
  • Evaluation strategy
  • LiDAR data
  • Point cloud

ASJC Scopus subject areas

  • Engineering(all)
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Fingerprint Dive into the research topics of 'Quantitative evaluation strategies for urban 3D model generation from remote sensing data'. Together they form a unique fingerprint.

  • Cite this