TY - JOUR
T1 - Reconstructing building mass models from UAV images
AU - Li, Minglei
AU - Nan, Liangliang
AU - Smith, Neil
AU - Wonka, Peter
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2015/7/26
Y1 - 2015/7/26
N2 - We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first generate a dense point cloud from the aerial images. Based on the statistical analysis of the footprint grid of the buildings, the point cloud is classified into different categories (i.e., buildings, ground, trees, and others). Roof structures are extracted for each individual building using Markov random field optimization. Then, a contour refinement algorithm based on pivot point detection is utilized to refine the contour of patches. Finally, polygonal mesh models are extracted from the refined contours. Experiments on various scenes as well as comparisons with state-of-the-art reconstruction methods demonstrate the effectiveness and robustness of the proposed method.
AB - We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first generate a dense point cloud from the aerial images. Based on the statistical analysis of the footprint grid of the buildings, the point cloud is classified into different categories (i.e., buildings, ground, trees, and others). Roof structures are extracted for each individual building using Markov random field optimization. Then, a contour refinement algorithm based on pivot point detection is utilized to refine the contour of patches. Finally, polygonal mesh models are extracted from the refined contours. Experiments on various scenes as well as comparisons with state-of-the-art reconstruction methods demonstrate the effectiveness and robustness of the proposed method.
UR - http://hdl.handle.net/10754/567059
UR - http://linkinghub.elsevier.com/retrieve/pii/S0097849315001077
UR - http://www.scopus.com/inward/record.url?scp=84939164993&partnerID=8YFLogxK
U2 - 10.1016/j.cag.2015.07.004
DO - 10.1016/j.cag.2015.07.004
M3 - Article
SN - 0097-8493
VL - 54
SP - 84
EP - 93
JO - Computers & Graphics
JF - Computers & Graphics
ER -