Real-time Halfway Domain Reconstruction of Motion and Geometry
Lucas Thies1 Michael Zollhöfer2 Christian Richardt2,3,4 Christian Theobalt2 Günther Greiner1
1 University of Erlangen-Nuremberg 2 MPI Informatik 3 Intel Visual Computing Institute 4 University of Bath
International Conference on 3D Vision (3DV) 2016
Abstract
We present a novel approach for real-time joint reconstruction of 3D scene motion and geometry from binocular stereo videos. Our approach is based on a novel variational halfway-domain scene flow formulation, which allows us to obtain highly accurate spatiotemporal reconstructions of shape and motion. We solve the underlying optimization problem at real-time frame rates using a novel data-parallel robust non-linear optimization strategy. Fast convergence and large displacement flows are achieved by employing a novel hierarchy that stores delta flows between hierarchy levels. High performance is obtained by the introduction of a coarser warp grid that decouples the number of unknowns from the input resolution of the images. We demonstrate our approach in a live setup that is based on two commodity webcams, as well as on publicly available video data. Our extensive experiments and evaluations show that our approach produces high-quality dense reconstructions of 3D geometry and scene flow at real-time frame rates, and compares favorably to the state of the art.
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- This paper on arXiv (arXiv:1610.07159)
Bibtex
@inproceedings{HalfwayDomainSceneFlow, author = {Lucas Thies and Michael Zollh{\"o}fer and Christian Richardt and Christian Theobalt and G{\"u}nther Greiner}, title = {Real-time Halfway Domain Reconstruction of Motion and Geometry}, booktitle = {International Conference on 3D Vision (3DV)}, year = {2016}, month = {October}, pages = {450--459}, doi = {10.1109/3DV.2016.55}, url = {http://richardt.name/publications/halfway-domain-scene-flow/}, }