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Papers

Semi-Dense 3D Reconstruction with a Stereo Event Camera

2018-07-19 · ECCV 2018 9 · Yi Zhou, Guillermo Gallego, Henri Rebecq, Laurent Kneip, Hongdong Li, Davide Scaramuzza

Event cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision. This paper presents a solution to the problem of 3D reconstruction from data captured by a stereo event-camera rig moving in a static scene, such as in the context of stereo Simultaneous Localization and Mapping. The proposed method consists of the optimization of an energy function designed to exploit small-baseline spatio-temporal consistency of events triggered across both stereo image planes. To improve the density of the reconstruction and to reduce the uncertainty of the estimation, a probabilistic depth-fusion strategy is also developed. The resulting method has no special requirements on either the motion of the stereo event-camera rig or on prior knowledge about the scene. Experiments demonstrate our method can deal with both texture-rich scenes as well as sparse scenes, outperforming state-of-the-art stereo methods based on event data image representations.

📄 PDF Abstract BibTeX arXiv:1807.07429

Code (4)

HKUST-Aerial-Robotics/ESVO
gogojjh/ESVO_extension
nail-hnu/esvio_aa
nail-hnu/esvo2

Tasks

3D ReconstructionSimultaneous Localization and Mapping

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