Space Location of Image in Urban Environments Based on C/S Structure

ZHANG Chunsen; WANG Xiqi; GUO Bingxuan

doi:10.13203/j.whugis20160455

Volume 43 Issue 7

Jul. 2018

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Geomatics and Information Science of Wuhan University > 2018 > 43(7): 978-983. > DOI: 10.13203/j.whugis20160455

ZHANG Chunsen, WANG Xiqi, GUO Bingxuan. Space Location of Image in Urban Environments Based on C/S Structure[J]. Geomatics and Information Science of Wuhan University, 2018, 43(7): 978-983. DOI: 10.13203/j.whugis20160455

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Space Location of Image in Urban Environments Based on C/S Structure

1.
College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
2.
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Funds:

The National Key Research and Development Program of China 2016YFB0502200

Surveying and Mapping Geographic Information Public Industry Research Projects 210600001

Guangzhou Science and Technology Plan 2017010160173

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Author Bio:
ZHANG Chunsen, PhD, professor, specializes in photogrammetry and remote sensing.E-mail:zhchunsen@aliyun.com
Corresponding author:
GUO Bingxuan, PhD, professor.E-mail:mobilemap@163.com
Received Date: March 12, 2017
Published Date: July 04, 2018

Graphical Abstract

Abstract

Abstract

Aiming at the low positioning accuracy of image space location in urban environments, this paper proposes a new method of space location of image in urban environments based on C/S structure. First, a series of indoor images are taken in advance. We use the nearest neighbor distance ratio (NNDR) and normalized cross correlation (NCC) to get the SIFT coarse matches, then use RANSAC method to optimize it, and calculate the fundamental matrix and projection matrix. Building 3D point cloud model is established, and the object space feature library including image feature points, image point coordinates and object space point coordinates are got. Second, we regard the building images which are taken by user's mobile phone as the location images. Image feature points of location images are extracted and matched with the feature points of object space feature library, then the object space point coordinates are obtained. Finally, we use collinearity equation model to accurately calculate the exterior orientation elements, and display the user's space position on the phone, thus space positioning is realized. The experimental results show that the positioning method in this paper can reach the centimeter level positioning accuracy, and can meet the requirements of the user positioning accuracy.
- space location,
- image matching,
- fundamental matrix,
- projection matrix,
- three-dimensional reconstruction,
- exterior orientation elements

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