Share Email Print
cover

Proceedings Paper

An automated 3D reconstruction method of UAV images
Author(s): Jun Liu; He Wang; Xiaoyang Liu; Feng Li; Guangtong Sun; Ping Song
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

Paper Details

Date Published: 8 October 2015
PDF: 6 pages
Proc. SPIE 9678, AOPC 2015: Telescope and Space Optical Instrumentation, 96780S (8 October 2015); doi: 10.1117/12.2199631
Show Author Affiliations
Jun Liu, Institute of Disaster Prevention Science and Technology (China)
He Wang, Institute of Disaster Prevention Science and Technology (China)
Xiaoyang Liu, Institute of Disaster Prevention Science and Technology (China)
Feng Li, Institute of Disaster Prevention Science and Technology (China)
Guangtong Sun, Institute of Disaster Prevention Science and Technology (China)
Ping Song, Institute of Disaster Prevention Science and Technology (China)


Published in SPIE Proceedings Vol. 9678:
AOPC 2015: Telescope and Space Optical Instrumentation
Bin Xiangli; Dae Wook Kim; Suijian Xue, Editor(s)

© SPIE. Terms of Use
Back to Top