Title
Transformation Model with Constraints for High-Accuracy of 2D-3D Building Registration in Aerial Imagery.
Abstract
This paper proposes a novel rigorous transformation model for 2D-3D registration to address the difficult problem of obtaining a sufficient number of well-distributed ground control points (GCPs) in urban areas with tall buildings. The proposed model applies two types of geometric constraints, co-planarity and perpendicularity, to the conventional photogrammetric collinearity model. Both types of geometric information are directly obtained from geometric building structures, with which the geometric constraints are automatically created and combined into the conventional transformation model. A test field located in downtown Denver, Colorado, is used to evaluate the accuracy and reliability of the proposed method. The comparison analysis of the accuracy achieved by the proposed method and the conventional method is conducted. Experimental results demonstrated that: (1) the theoretical accuracy of the solved registration parameters can reach 0.47 pixels, whereas the other methods reach only 1.23 and 1.09 pixels; (2) the RMS values of 2D-3D registration achieved by the proposed model are only two pixels along the x and y directions, much smaller than the RMS values of the conventional model, which are approximately 10 pixels along the x and y directions. These results demonstrate that the proposed method is able to significantly improve the accuracy of 2D-3D registration with much fewer GCPs in urban areas with tall buildings.
Year
DOI
Venue
2016
10.3390/rs8060507
REMOTE SENSING
Keywords
Field
DocType
2D-3D registration,transformation model,building,aerial image,urban
Photogrammetry,Computer vision,Collinearity,Remote sensing,Aerial image,Root mean square,Artificial intelligence,Pixel,Geology,Aerial imagery
Journal
Volume
Issue
Citations 
8
6
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Guoqing Zhou12515.98
qingli luo2173.40
Wenhan Xie300.34
Tao Yue454.44
Jingjin Huang5124.04
Yuzhong Shen618421.96