Precise indoor localization with 3D facility scan data

Jiahao Xia, Jie Gong

Research output: Contribution to journalArticlepeer-review


Visual indoor localization for smart indoor services is a growing field of interest as cameras are now ubiquitously equipped on smartphones. In this study, a hierarchical indoor localization algorithm is designed and validated based on 3D facility scan data, which are originally collected for facility modeling purposes. The study has shown promising results in indoor localization. The study also demonstrated a scalable approach to generate high-quality images with reference poses from laser scan data, opening doors to generate labeled images to train end-to-end pose regression model (i.e., PoseNet). In this regard, this study is the first attempt to leverage facility scan data, which are commonly collected for Building Information Modeling (BIM) purpose, for indoor localization. As more facilities are documented with laser scanners, our algorithm can unlock additional values of collected data for intelligent applications.

Original languageAmerican English
Pages (from-to)1243-1259
Number of pages17
JournalComputer-Aided Civil and Infrastructure Engineering
Issue number10
StatePublished - Aug 2022

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics


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