Publication:Semi-Dense 3D Reconstruction with a Stereo Event Camera

Publication: Semi-Dense 3D Reconstruction with a Stereo Event Camera

Authors: Zhou, Yi; Gallego, Guillermo; Rebecq, Henri; Kneip, Laurent; Li, Hongdong; Scaramuzza, Davide

 

  • Presented at: European Conference on Computer Vision (ECCV), Munich, 2018

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.

Reference

  • Detailed record: arXiv
  • Date: 2018
Posted on: January 4, 2019