TY - GEN
T1 - Least commitment, viewpoint-based, multi-view stereo
AU - Hu, Xiaoyan
AU - Mordohai, Philippos
PY - 2012
Y1 - 2012
N2 - We address the problem of large-scale 3D reconstruction from calibrated images relying on a viewpoint-based approach. The representation is in the form of a collection of depth maps, which are fused to blend consistent depth estimates and minimize violations of visibility constraints. We adopt a least commitment strategy by allowing multiple candidate depth values per pixel in the fusion process and deferring hard decisions as much as possible. To address the inevitable noise in the depth maps, we explicitly model its sources, namely mismatches and inaccurate 3D coordinate estimation via triangulation, by measuring two types of uncertainty and using the uncertainty estimates to guide the fusion process. To the best of our knowledge, this is the first attempt to model both geometric and correspondence uncertainty in the context of dense 3D reconstruction. We show quantitative results on datasets with ground truth that are competitive with the state of the art.
AB - We address the problem of large-scale 3D reconstruction from calibrated images relying on a viewpoint-based approach. The representation is in the form of a collection of depth maps, which are fused to blend consistent depth estimates and minimize violations of visibility constraints. We adopt a least commitment strategy by allowing multiple candidate depth values per pixel in the fusion process and deferring hard decisions as much as possible. To address the inevitable noise in the depth maps, we explicitly model its sources, namely mismatches and inaccurate 3D coordinate estimation via triangulation, by measuring two types of uncertainty and using the uncertainty estimates to guide the fusion process. To the best of our knowledge, this is the first attempt to model both geometric and correspondence uncertainty in the context of dense 3D reconstruction. We show quantitative results on datasets with ground truth that are competitive with the state of the art.
KW - 3D reconstruction
KW - depth map fusion
KW - stereo vision
UR - http://www.scopus.com/inward/record.url?scp=84872049965&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84872049965&partnerID=8YFLogxK
U2 - 10.1109/3DIMPVT.2012.60
DO - 10.1109/3DIMPVT.2012.60
M3 - Conference contribution
AN - SCOPUS:84872049965
SN - 9780769548739
T3 - Proceedings - 2nd Joint 3DIM/3DPVT Conference: 3D Imaging, Modeling, Processing, Visualization and Transmission, 3DIMPVT 2012
SP - 531
EP - 538
BT - Proceedings - 2nd Joint 3DIM/3DPVT Conference
T2 - 2nd Joint 3DIM/3DPVT Conference: 3D Imaging, Modeling, Processing, Visualization and Transmission, 3DIMPVT 2012
Y2 - 13 October 2012 through 15 October 2012
ER -