Decentralized Fusion of 3D Extended Object Tracking Based on a B-Spline Shape Model

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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Publication Details

Published
2025-09-08
DOI
https://doi.org/10.23919/eusipco63237.2025.11226593
Primary Topic
Video Surveillance and Tracking Methods
Type
article
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article

Decentralized Fusion of 3D Extended Object Tracking Based on a B-Spline Shape Model

Klaus Kefferpütz, Longfei Han, Jürgen Beyerer
Video Surveillance and Tracking Methods
article

Decentralized Fusion of 3D Extended Object Tracking Based on a B-Spline Shape Model

Klaus Kefferpütz, Longfei Han, Jürgen Beyerer
article en

Abstract

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.

Karlsruhe Institute of Technology (DE), Technische Hochschule Ingolstadt (DE)
Openalex Percentile: Top 60%
Video Surveillance and Tracking Methods
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