用B样条建模3D目标轮廓，实现分布式融合跟踪
Decentralized Fusion of 3D Extended Object Tracking based on a B-Spline Shape Model
- 用B样条拟合目标侧视轮廓并拉伸成3D形状
- 基于协方差交集的分布式融合提升视角不利传感器性能
- 适用于交通场景下多源感知的鲁棒跟踪系统
扩展目标跟踪（EOT）利用现代传感器的高分辨率实现更精细的环境感知。结合分布式融合，可构建更可扩展、更鲁棒的感知系统。本文研究基于B样条形状模型的3D EOT分布式融合方法。通过样条曲线表示目标侧视轮廓，并沿宽度方向挤出形成3D形状。采用协方差交集（CI）进行分布式融合，探讨其在EOT中的应用挑战。在模拟与真实交通场景数据集上评估融合效果，结果表明，基于CI的融合能显著提升视角不利传感器的跟踪性能。
原文摘要 · Abstract (English)
Extended Object Tracking (EOT) exploits the high resolution of modern sensors for detailed environmental perception. Combined with decentralized fusion, it contributes to a more scalable and robust perception system. This paper investigates the decentralized fusion of 3D EOT using a B-spline curve based model. The spline curve is used to represent the side-view profile, which is then extruded with a width to form a 3D shape. We use covariance intersection (CI) for the decentralized fusion and discuss the challenge of applying it to EOT. We further evaluate the tracking result of the decentralized fusion with simulated and real datasets of traffic scenarios. We show that the CI-based fusion can significantly improve the tracking performance for sensors with unfavorable perspective.
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