ステレオイベントカメラによる半密3D再構成
Semi-Dense 3D Reconstruction with a Stereo Event Camera
ステレオイベントカメラの両眼イベントの時空間一貫性を利用したエネルギー最適化と確率的深度融合により、テクスチャ豊富な場面から疎な場面まで対応する半密な3D再構成手法を提案した。
著者: Yi Zhou, Guillermo Gallego, Henri Rebecq, Laurent Kneip, Hongdong Li, Davide Scaramuzza
分類: cs.CV, cs.RO
原文アブストラクト
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.
