TY - GEN
T1 - Correcting for duplicate scene structure in sparse 3D reconstruction
AU - Heinly, Jared
AU - Dunn, Enrique
AU - Frahm, Jan Michael
PY - 2014
Y1 - 2014
N2 - Structure from motion (SfM) is a common technique to recover 3D geometry and camera poses from sets of images of a common scene. In many urban environments, however, there are symmetric, repetitive, or duplicate structures that pose challenges for SfM pipelines. The result of these ambiguous structures is incorrectly placed cameras and points within the reconstruction. In this paper, we present a post-processing method that can not only detect these errors, but successfully resolve them. Our novel approach proposes the strong and informative measure of conflicting observations, and we demonstrate that it is robust to a large variety of scenes.
AB - Structure from motion (SfM) is a common technique to recover 3D geometry and camera poses from sets of images of a common scene. In many urban environments, however, there are symmetric, repetitive, or duplicate structures that pose challenges for SfM pipelines. The result of these ambiguous structures is incorrectly placed cameras and points within the reconstruction. In this paper, we present a post-processing method that can not only detect these errors, but successfully resolve them. Our novel approach proposes the strong and informative measure of conflicting observations, and we demonstrate that it is robust to a large variety of scenes.
KW - Structure from motion
KW - duplicate structure disambiguation
UR - http://www.scopus.com/inward/record.url?scp=84906519035&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84906519035&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-10593-2_51
DO - 10.1007/978-3-319-10593-2_51
M3 - Conference contribution
AN - SCOPUS:84906519035
SN - 9783319105925
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 780
EP - 795
BT - Computer Vision, ECCV 2014 - 13th European Conference, Proceedings
T2 - 13th European Conference on Computer Vision, ECCV 2014
Y2 - 6 September 2014 through 12 September 2014
ER -