@inproceedings{2021_Thormann,
author = {Thormann, Kolja and Baum, Marcus},
booktitle = {2021 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)},
title = {Incorporating Range-Rate Measurements in {EKF}-based Elliptical Extended Object Tracking},
year = {2021},
month = sep
}
Kalman Filter Based Extended Object Tracking with a Gaussian Mixture Spatial Distribution Model
@inproceedings{2020_Fusion_Thormann,
author = {Thormann, Kolja and Yang, Shishan and Baum, Marcus},
booktitle = {Proceedings of the 23rd International Conference on Information Fusion (Fusion 2020)},
title = {A Comparison of Kalman Filter-based Approaches for Elliptic Extended Object Tracking},
year = {2020},
address = {Virtual},
month = jul,
code = {https://github.com/Fusion-Goettingen/KalmanEllipses},
doi = {10.23919/FUSION45008.2020.9190375}
}
Optimal Fusion of Elliptic Extended Target Estimates Based on the Wasserstein Distance
K. Thormann and M. Baum
22nd International Conference on Information Fusion (FUSION 2019), Ottawa, Canada, 2019.
This paper considers the fusion of multiple estimates of a spatially extended object, where the object extent is modeled as an ellipse parameterized by the orientation and semi-axes lengths. For this purpose, we propose a novel systematic approach that employs a distance measure for ellipses, i.e., the Gaussian Wasserstein distance, as a cost function. We derive an explicit approximate expression for the Minimum Mean Gaussian Wasserstein distance (MMGW) estimate. Based on the concept of a MMGW estimator, we develop efficient methods for the fusion of extended target estimates. The proposed fusion methods are evaluated in a simulated experiment and the benefits of the novel methods are discussed.
@inproceedings{2019_Fusion_Thormann,
author = {Thormann, Kolja and Baum, Marcus},
title = {Optimal Fusion of Elliptic Extended Target Estimates Based on the Wasserstein Distance},
booktitle = {22nd International Conference on Information Fusion (FUSION 2019)},
year = {2019},
address = {Ottawa, Canada},
month = jul,
code = {https://github.com/Fusion-Goettingen/ExtendedObjectTracking/tree/master/EllipseFusion},
days = {2},
url = {https://arxiv.org/abs/1904.00708}
}
Linear-Time Joint Probabilistic Data Association for Multiple Extended Object Tracking
S. Yang, K. Thormann, and M. Baum
2018 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2018), Sheffield, United Kingdom, 2018.
@inproceedings{Yang2018_SAM,
author = {Yang, Shishan and Thormann, Kolja and Baum, Marcus},
booktitle = {2018 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2018)},
title = {{Linear-Time Joint Probabilistic Data Association for Multiple Extended Object Tracking}},
year = {2018},
address = {Sheffield, United Kingdom},
month = jul,
code = {https://github.com/Fusion-Goettingen/ExtendedObjectTracking/tree/master/MEOT/linearJPDA},
days = {7},
doi = {10.1109/sam.2018.8448430}
}
Extended Target Tracking Using Gaussian Processes with High-Resolution Automotive Radar
K. Thormann, J. Honer, and M. Baum
21st International Conference on Information Fusion (FUSION 2018), Cambridge, United Kingdom, 2018.
@inproceedings{Thormann2018_Fusion,
author = {Thormann, Kolja and Honer, Jens and Baum, Marcus},
title = {{Extended Target Tracking Using Gaussian Processes with {High-Resolution} Automotive Radar}},
booktitle = {21st International Conference on Information Fusion (FUSION 2018)},
year = {2018},
address = {Cambridge, United Kingdom},
month = jul
}
Fast Road Boundary Detection and Tracking in Occupancy Grids from Laser Scans
K. Thormann, J. Honer, and M. Baum
Proceedings of the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017), Daegu, Korea, 2017.
@inproceedings{Thormann2017a,
author = {Thormann, Kolja and Honer, Jens and Baum, Marcus},
title = {{Fast Road Boundary Detection and Tracking in Occupancy Grids from Laser Scans}},
booktitle = {Proceedings of the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017)},
year = {2017},
address = {Daegu, Korea},
month = nov,
doi = {10.1109/MFI.2017.8170453}
}
Learning an Object Tracker with a Random Forest and Simulated Measurements
K. Thormann, F. Sigges, and M. Baum
Proceedings of the 20th International Conference on Information Fusion (FUSION 2017), Xi’an, P.R. China, 2017.
@inproceedings{Thormann2017,
author = {Thormann, Kolja and Sigges, Fabian and Baum, Marcus},
title = {{Learning an Object Tracker with a Random Forest and Simulated Measurements}},
booktitle = {Proceedings of the 20th International Conference on Information Fusion (FUSION 2017)},
year = {2017},
address = {Xi'an, P.R. China},
month = jul,
days = {9},
doi = {10.23919/ICIF.2017.8009674}
}
@inproceedings{2021_Wolf,
author = {Wolf, Laura and Baum, Marcus},
booktitle = {Proceedings of the 24th International Conference on Information Fusion (Fusion 2021)},
title = {Continuous Herded {G}ibbs Sampling},
year = {2021},
address = {South Africa},
month = nov
}
Deterministic Gibbs Sampling for Data Association in Multi-Object Tracking
L. Wolf and M. Baum
Proceedings of the 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2020), Virtual, 2020.
@inproceedings{2020_Wolf,
author = {Wolf, Laura and Baum, Marcus},
booktitle = {Proceedings of the 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2020)},
title = {Deterministic Gibbs Sampling for Data Association in Multi-Object Tracking},
year = {2020},
address = {Virtual},
month = sep,
code = {https://github.com/Fusion-Goettingen/HerdedGibbs},
doi = {10.1109/MFI49285.2020.9235211},
url = {https://www.techrxiv.org/articles/Deterministic_Gibbs_Sampling_for_Data_Association_in_Multi-Object_Tracking/12435398/1}
}
Marginal Association Probabilities for Multiple Extended Objects without Enumeration of Measurement Partitions
S. Yang, L. M. Wolf, and M. Baum
Proceedings of the 23rd International Conference on Information Fusion (Fusion 2020), Virtual, 2020.
@inproceedings{2020_Fusion_Yang,
author = {Yang, Shishan and Wolf, Laura M. and Baum, Marcus},
booktitle = {Proceedings of the 23rd International Conference on Information Fusion (Fusion 2020)},
title = {{Marginal Association Probabilities for Multiple Extended Objects without Enumeration of Measurement Partitions}},
year = {2020},
address = {Virtual},
month = jul,
doi = {10.23919/FUSION45008.2020.9190500}
}
External PhD students
Jaya Shradha Fowdur, M. Sc.
Affiliation
German Aerospace Center (DLR), Institute of Communications and Navigation, Nautical Systems, Neustrelitz
