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Scene Flow

Background: 
Andreas Görlitz, Jonas Geiping, Andreas Kolb:
Piecewise Rigid Scene Flow with Implicit Motion Segmentation
International Conference on Intelligent Robots and Systems (IROS), 2019
Abstract: In this paper, we introduce a novel variational approach to estimate the scene flow from RGB-D images. We regularize the ill-conditioned problem of scene flow estimation in a unified framework by enforcing piecewise rigid motion through decomposition into rotational and translational motion parts. Our model crucially regularizes these components by an L0 norm, thereby facilitating implicit motion segmentation in a joint energy minimization problem. Yet, we also show that this energy can be efficiently minimized by a proximal primal-dual algorithm. By implementing this approximate L0 rigid motion regularization, our scene flow estimation approach implicitly segments the observed scene of into regions of nearly constant rigid motion. We evaluate our joint scene flow and segmentation estimation approach on a variety of test scenarios, with and without ground truth data, and demonstrate that we outperform current scene flow techniques.
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Publications: 


2019

Conference Papers

[bib] - Andreas Görlitz, Jonas Geiping, Andreas Kolb - Piecewise Rigid Scene Flow with Implicit Motion Segmentation
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019