Jun 21, 2021 · We propose a no-reference metric, Mutually Orthogonal Metric (MOM), that estimates the quality of the map from registered point clouds via the trajectory poses.
Abstract—This paper addresses the problem of assessing trajectory quality in conditions when no ground truth poses are available or when their accuracy is ...
A no-reference metric, Mutually Orthogonal Metric (MOM), that estimates the quality of the map from registered point clouds via the trajectory poses, ...
Jun 21, 2021 · This paper addresses the problem of assessing trajectory quality in conditions when no ground truth poses are available or when their ...
Map metrics toolkit provides a set of metrics to quantitatively evaluate trajectory quality via estimating consistency of the map aggregated from point clouds.
MOM (Mutually Orthogonal Metric) is a metric that evaluates trajectory quality via estimation inconsistency of the map aggregated from registered point clouds.
Be your own Benchmark: No-Reference Trajectory Metric on Registered Point Clouds. A Kornilova, G Ferrer. 2021 European Conference on Mobile Robots (ECMR), 2021.
from publication: Be your own Benchmark: No-Reference Trajectory Metric on Registered Point Clouds | This paper addresses the problem of assessing trajectory ...
Be your own Benchmark: No-Reference Trajectory Metric on Registered Point Clouds · A. KornilovaG. Ferrer. Computer Science, Engineering. 2021 European ...
May 10, 2024 · Using these ground truth labels, we train multiple state-of-the-art deep learning models for MBES registration, and evaluate both classical and ...
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