Indoor Navigation Elements Extraction of Room Fineness Using Refining Space Separator Method

LIU Minglei; WEI Shuangfeng; HUANG Shuai; TANG Nian

doi:10.13203/j.whugis20190223

Volume 46 Issue 2

Jan. 2021

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Geomatics and Information Science of Wuhan University > 2021 > 46(2): 221-229. > DOI: 10.13203/j.whugis20190223

LIU Minglei, WEI Shuangfeng, HUANG Shuai, TANG Nian. Indoor Navigation Elements Extraction of Room Fineness Using Refining Space Separator Method[J]. Geomatics and Information Science of Wuhan University, 2021, 46(2): 221-229. DOI: 10.13203/j.whugis20190223

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Indoor Navigation Elements Extraction of Room Fineness Using Refining Space Separator Method

LIU Minglei^1,,
WEI Shuangfeng^{1, 2, 3, 4, ,},
HUANG Shuai¹,
TANG Nian¹

1.
School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 102616, China
2.
Engineering Research Center of Representative Building and Architectural Heritage Database, Ministry of Education, Beijing 102616, China
3.
Key Laboratory for Urban Spatial Informatics of Ministry of Natural Resources, Beijing 102616, China
4.
Beijing Key Laboratory for Architectural Heritage Fine Reconstruction & Health Monitoring, Beijing 102616, China

Funds:

The National Key Research and Development Program of China 2016YFC0702107

he Postgraduate Innovation Research Project of Beijing University of Civil Engineering and Architecture PG2019058

he Postgraduate Innovation Research Project of Beijing University of Civil Engineering and Architecture PG2019061

he Postgraduate Innovation Research Project of Beijing University of Civil Engineering and Architecture PG2019065

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Author Bio:
LIU Minglei, master, specializes in 3D indoor navigation modeling based on point cloud. E-mail: Liuminglei1009@163.com
Corresponding author:
WEi Shuangfeng, PhD, associate professor. E-mail:weishuangfeng@bucea.edu.cn
Received Date: December 06, 2019
Published Date: February 04, 2021

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Abstract

Abstract

In the existing methods of indoor 3D model reconstruction, indoor navigation elements that work as space separators are usually regarded as undividable structure. However, the shape difference between two wall surfaces on one wall will cause details loss in the indoor 3D reconstruction room extraction, as well as difficulties in extracting doors and windows. Aiming to solve this problem, this paper proposes an idea of refining space separator. By refining one wall into two wall surfaces, regional growth algorithm is applied to obtain the corner points of inner wall, so that the refined expression of the interior can be obtained. Point cloud densities of corresponding areas on two wall surfaces are compared to avoid the influence of the obstacles blocking the wall surface on the extraction result of door and window extraction. The results show that the proposed method can effectively extract indoor doors and windows, which provides an important basis for the generation of navigation network.
- point cloud,
- indoor navigation elements,
- refined space separator,
- regional growth algorithm

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References (20)

References

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