# 3D Extended Object Tracking based on Extruded B-Spline Side View Profiles

arXiv: https://arxiv.org/abs/2503.10730 · HTML: https://mlsanity.com/paper/2503.10730/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 29 references that are in the map.
- First posted on arXiv 13 Mar 2025.

## Builds on (most cited first, 5 of 5)

- [CARLA: An Open Urban Driving Simulator](https://mlsanity.com/paper/1711.03938/) (2017)
- [Extended Object Tracking: Introduction, Overview and Applications](https://mlsanity.com/paper/1604.00970/) (2016)
- [Scalable Detection and Tracking of Geometric Extended Objects](https://mlsanity.com/paper/2103.11279/) (2021)
- [Fast 3D Extended Target Tracking using NURBS Surfaces](https://mlsanity.com/paper/1909.00767/) (2019)
- [Three-dimensional Simultaneous Shape and Pose Estimation for Extended Objects Using Spherical Harmonics](https://mlsanity.com/paper/2012.13580/) (2020)

## Abstract (arXiv)

Object tracking is an essential task for autonomous systems. With the advancement of 3D sensors, these systems can better perceive their surroundings using effective 3D Extended Object Tracking (EOT) methods. Based on the observation that common road users are symmetrical on the right and left sides in the traveling direction, we focus on the side view profile of the object. In order to leverage of the development in 2D EOT and balance the number of parameters of a shape model in the tracking algorithms, we propose a method for 3D extended object tracking (EOT) by describing the side view profile of the object with B-spline curves and forming an extrusion to obtain a 3D extent. The use of B-spline curves exploits their flexible representation power by allowing the control points to move freely. The algorithm is developed into an Extended Kalman Filter (EKF). For a through evaluation of this method, we use simulated traffic scenario of different vehicle models and realworld open dataset containing both radar and lidar data.