A motion uncertainty estimation method is proposed to derive uncertainty from the residual between optical flow and camera motion induced flow, directly reflecting object motion, to derive uncertainty from the residual between optical flow and camera motion induced flow for dynamic scenes.
Dense visual odometry (VO), which provides pose estimation and dense 3D reconstruction, serves as the cornerstone for applications ranging from robotics to augmented reality. Recently, feed-forward models have demonstrated remarkable capabilities in dense mapping. However, when these models are used in dense visual SLA...
Jun-Xiang Pang, Lipu Zhou, Bao-Jie Chen et al.· IEEE Robotics and Automation...· 0 citations
Geometry-only Gaussian Splatting (GeoGS), which directly reconstructs scene geometry, and GeoGS-SLAM, a dense visual SLAM system built upon this representation, which outperforms SOTA methods in terms of online mapping efficiency and geometric reconstruction quality.
Lipu Zhou, Yaoyun Kang, Junxiang Pang et al.· arXiv.org· 0 citations
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