Image-based indoor localization using BIM and features of CNN

Inhae Ha; Hongjo Kim; Somin Park; Hyoungkwan Kim

doi:10.22260/isarc2018/0107

Image-based indoor localization using BIM and features of CNN

Inhae Ha, Hongjo Kim, Somin Park, Hyoungkwan Kim

Department of Civil and Environmental Engineering

Research output: Contribution to conference › Paper › peer-review

5 Citations (Scopus)

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 language	English
DOIs	https://doi.org/10.22260/isarc2018/0107
Publication status	Published - 2018
Event	35th 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 20 → 2018 Jul 25

Other

Other	35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018
Country/Territory	Germany
City	Berlin
Period	18/7/20 → 18/7/25

Bibliographical note

Funding Information:
This work was supported by a grant (18CTAP-C133290-02) from Infrastructure and transportation technology promotion research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Publisher Copyright:
© ISARC 2018 - 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things. All rights reserved.

All Science Journal Classification (ASJC) codes

Computer Vision and Pattern Recognition
Artificial Intelligence
Building and Construction

Access to Document

10.22260/isarc2018/0107

Cite this

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AU - Kim, Hongjo

AU - Park, Somin

AU - Kim, Hyoungkwan

N1 - Funding Information: This work was supported by a grant (18CTAP-C133290-02) from Infrastructure and transportation technology promotion research Program funded by Ministry of Land, Infrastructure and Transport of Korean government. Publisher Copyright: © ISARC 2018 - 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things. All rights reserved.

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

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Y2 - 20 July 2018 through 25 July 2018

ER -

Image-based indoor localization using BIM and features of CNN

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Bibliographical note

All Science Journal Classification (ASJC) codes

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