TY - GEN
T1 - Discrete laplace operator estimation for dynamic 3D reconstruction
AU - Xu, Xiangyu
AU - Dunn, Enrique
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - We present a general paradigm for dynamic 3D reconstruction from multiple independent and uncontrolled image sources having arbitrary temporal sampling density and distribution. Our graph-theoretic formulation models the spatio-temporal relationships among our observations in terms of the joint estimation of their 3D geometry and its discrete Laplace operator. Towards this end, we define a tri-convex optimization framework that leverages the geometric properties and dependencies found among a Euclidean shape-space and the discrete Laplace operator describing its local and global topology. We present a reconstructability analysis, experiments on motion capture data and multi-view image datasets, as well as explore applications to geometry-based event segmentation and data association.
AB - We present a general paradigm for dynamic 3D reconstruction from multiple independent and uncontrolled image sources having arbitrary temporal sampling density and distribution. Our graph-theoretic formulation models the spatio-temporal relationships among our observations in terms of the joint estimation of their 3D geometry and its discrete Laplace operator. Towards this end, we define a tri-convex optimization framework that leverages the geometric properties and dependencies found among a Euclidean shape-space and the discrete Laplace operator describing its local and global topology. We present a reconstructability analysis, experiments on motion capture data and multi-view image datasets, as well as explore applications to geometry-based event segmentation and data association.
UR - http://www.scopus.com/inward/record.url?scp=85081912240&partnerID=8YFLogxK
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U2 - 10.1109/ICCV.2019.00163
DO - 10.1109/ICCV.2019.00163
M3 - Conference contribution
AN - SCOPUS:85081912240
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 1548
EP - 1557
BT - Proceedings - 2019 International Conference on Computer Vision, ICCV 2019
T2 - 17th IEEE/CVF International Conference on Computer Vision, ICCV 2019
Y2 - 27 October 2019 through 2 November 2019
ER -