Image-based indoor localization using BIM and features of CNN

Inhae Ha, Hongjo Kim, Somin Park, Hyoungkwan Kim

Research output: Contribution to conferencePaper

Abstract

This study suggests an indoor localization method to estimate the location of a user of a mobile device with imaging capability. The proposed method uses a matching approach between an actual photograph and a rendered BIM (building information modeling) image. A pre-trained VGG 16 network is used for feature extraction. Experimental results show that the best image matching performance can be obtained when using features from pooling layer 4 of VGG16. The proposed method allows for indoor localization only by image matching without additional sensing information.

Original languageEnglish
Publication statusPublished - 2018 Jan 1
Event35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018 - Berlin, Germany
Duration: 2018 Jul 202018 Jul 25

Other

Other35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018
CountryGermany
CityBerlin
Period18/7/2018/7/25

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All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Building and Construction

Cite this

Ha, I., Kim, H., Park, S., & Kim, H. (2018). Image-based indoor localization using BIM and features of CNN. Paper presented at 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018, Berlin, Germany.