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ClusterSLAM: A SLAM backend for simultaneous rigid body clustering and motion estimation
2021
Computational Visual Media
AbstractWe present a practical backend for stereo visual SLAM which can simultaneously discover individual rigid bodies and compute their motions in dynamic environments. While recent factor graph based state optimization algorithms have shown their ability to robustly solve SLAM problems by treating dynamic objects as outliers, their dynamic motions are rarely considered. In this paper, we exploit the consensus of 3D motions for landmarks extracted from the same rigid body for clustering, and
doi:10.1007/s41095-020-0195-3
fatcat:hip62un4fzc4bchigrgj7aaoce