DynamicGlue: Epipolar and Time-Informed Data Association in Dynamic Environments using Graph Neural Networks

arXiv:2403.11370v1 Announce Type: new
Abstract: The assumption of a static environment is common in many geometric computer vision tasks like SLAM but limits their applicability in highly dynamic scenes. Since these tasks rely on identifying point correspondences between input images within the static part of the environment, we propose a graph neural network-based sparse feature matching network designed to perform robust matching under challenging conditions while excluding keypoints on moving objects. We employ a similar scheme of attentional aggregation over …

abstract arxiv association computer computer vision cs.cv cs.ro data dynamic environment environments graph graph neural networks images networks neural networks part slam tasks the environment type vision