Data Fusion

Welcome to the Data Fusion Lab!

The Data Fusion Lab was founded by Prof. Dr.-Ing. Marcus Baum in 2015. The group investigates novel methods for sensor data processing and fusion, i.e., signal and image processing, state estimation, and machine learning. A special focus of the group are tracking problems, i.e., the successive localization of one or more mobile objects. A typical application is environment perception of autonomous systems such as intelligent vehicles.


News

  • April 15, 2025:

    Lukas Steinegger joins the Data Fusion Lab.

  • August 15, 2024:

    PhD defense of Fabian Sigges with the title “Simulation-based Data Fusion and Tracking”

  • December 1, 2023:

    Aaron Kurda joins the Data Fusion Lab.

  • November 30, 2023:

    The paper “Single-Frame Radar Odometry Incorporating Bearing Uncertainty” by K. Thormann and M. Baum receives the award for the Best Paper, 2nd Runner Up at the Combined IEEE MFI/SDF conference.

  • May 1, 2023:

    The paper “The Kernel-SME Filter with Adaptive Kernel Widths for Association-free Multi-target Tracking” by E. Ernst, F. Pfaff, U. D. Hanebeck, and M. Baum is among the five finalists for the Best Student Paper Award of the ACC 2023 conference in San Diego.

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