Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1925-1929, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1925-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1925-1929, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1925-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

AUTOMATIC MATCHING OF LARGE SCALE IMAGES AND TERRESTRIAL LIDAR BASED ON APP SYNERGY OF MOBILE PHONE

G. Xia1,2,3 and C. Hu1,2,3 G. Xia and C. Hu
  • 1School of Geomantic and Urban Information, Beijing University of Civil Engineering and Architecture, NO.15Yongyuan Road, Daxing District, Beijing, 102616, China
  • 2Beijing, Key Laboratory for fine reconstruction and health monitoring of Architectural Heritage, NO.15Yongyuan Road, Daxing District, Beijing, 102616, China
  • 3Engineering Research Center of Representative Building and Architectural Heritage Database, Ministry of Education, Beijing, 102616, China

Keywords: Mobile phone APP, Images, Laser Point Cloud, Matching

Abstract. The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.