基于NURBS曲面的快速三维扩展目标跟踪
Fast 3D Extended Target Tracking using NURBS Surfaces
摘要：
本文提出了快速和新颖的方法来联合估计目标的未知三维形状和动态。测量是来自光探测和测距（LiDAR）传感器的噪声和稀疏分布的3D点。该方法利用非均匀有理B样条（NURBS）曲面来近似目标的形状。一种方法估计NURBS曲面的笛卡尔缩放参数，而第二种方法也估计相应的NURBS权重。主要优点是能够估计完全3D形状以及快速处理时间。与最先进的3D扩展目标跟踪算法相比，静态和动态车辆的实际评估显示出有希望的结果。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
