TY - GEN
T1 - Fast and seamless large-scale aerial 3d reconstruction using graph framework
AU - Xie, Xiuchuan
AU - Yang, Tao
AU - Li, Jing
AU - Ren, Qiang
AU - Zhang, Yanning
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/2/24
Y1 - 2018/2/24
N2 - Large-scale 3D reconstruction for aerial photography is achallenging. For aerial image dataset, large scale means that the amount and resolution of images are enormous, which brings a huge amount of computation in Structure from Motion (SfM) pipeline, especially on the process of feature detection, feature matching and bundle adjustment (BA). In this paper, we present a novel method to solve the large-scale 3D reconstruction in parallel to accelerate the process. It could be generalized as the process of Divide-Reconstruct-Optimize-Fuse. We propose an effective graph-based framework that could robustly conduct aerial images grouping task and optimize parameters to fuse sub-models seamless. Experimental results on large-scale aerial datasets demonstrate the efficiency and robustness of the proposed method.
AB - Large-scale 3D reconstruction for aerial photography is achallenging. For aerial image dataset, large scale means that the amount and resolution of images are enormous, which brings a huge amount of computation in Structure from Motion (SfM) pipeline, especially on the process of feature detection, feature matching and bundle adjustment (BA). In this paper, we present a novel method to solve the large-scale 3D reconstruction in parallel to accelerate the process. It could be generalized as the process of Divide-Reconstruct-Optimize-Fuse. We propose an effective graph-based framework that could robustly conduct aerial images grouping task and optimize parameters to fuse sub-models seamless. Experimental results on large-scale aerial datasets demonstrate the efficiency and robustness of the proposed method.
KW - Graph Framework
KW - Large-scale Aerial 3D Reconstruction
KW - Seamless Fusion
UR - https://www.scopus.com/pages/publications/85047323535
U2 - 10.1145/3191442.3191448
DO - 10.1145/3191442.3191448
M3 - 会议稿件
AN - SCOPUS:85047323535
T3 - ACM International Conference Proceeding Series
SP - 126
EP - 130
BT - Proceedings of 2018 International Conference on Image and Graphics Processing, ICIGP 2018
PB - Association for Computing Machinery
T2 - 2018 International Conference on Image and Graphics Processing, ICIGP 2018
Y2 - 24 February 2018 through 26 February 2018
ER -