This paper proposes fast and novel methods to jointly estimate the target's unknown 3D shape and dynamics. Measurements are noisy and sparsely distributed 3D points from a light detection and ranging (LiDAR) sensor. The methods utilize non-uniform rational B-splines (NURBS) surfaces to approximate the target's shape. One method estimates Cartesian scaling parameters of a NURBS surface, whereas the second method estimates the corresponding NURBS weights, too. Major advantages are the capability of estimating a fully 3D shape as well as the fast processing time. Real-world evaluations with a static and dynamic vehicle show promising results compared to state-of-the-art 3D extended target tracking algorithms.
@article{arxiv.1909.00767,
title = {Fast 3D Extended Target Tracking using NURBS Surfaces},
author = {Benjamin Naujoks and Patrick Burger and Hans-Joachim Wuensche},
journal= {arXiv preprint arXiv:1909.00767},
year = {2020}
}
Comments
In Proceedings of IEEE Intelligent Transportation Systems Conference (ITSC), 2019