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Stephan Reuter
Stephan Reuter
Sensor Fusion for Urban Automated Driving, Robert Bosch GmbH
Verified email at stephanreuter.de
Title
Cited by
Cited by
Year
The labeled multi-Bernoulli filter
S Reuter, BT Vo, BN Vo, K Dietmayer
IEEE Transactions on Signal Processing 62 (12), 3246-3260, 2014
8432014
Extended object tracking: Introduction, overview and applications
K Granstrom, M Baum, S Reuter
arXiv preprint arXiv:1604.00970, 2016
5172016
Multiple extended target tracking with labeled random finite sets
M Beard, S Reuter, K Granström, BT Vo, BN Vo, A Scheel
IEEE Transactions on Signal Processing 64 (7), 1638-1653, 2015
2672015
A random finite set approach for dynamic occupancy grid maps with real-time application
D Nuss, S Reuter, M Thom, T Yuan, G Krehl, M Maile, A Gern, ...
The International Journal of Robotics Research 37 (8), 841-866, 2018
1762018
Autonomous driving at Ulm University: A modular, robust, and sensor-independent fusion approach
F Kunz, D Nuss, J Wiest, H Deusch, S Reuter, F Gritschneder, A Scheel, ...
2015 IEEE intelligent vehicles symposium (IV), 666-673, 2015
1502015
The labeled multi-Bernoulli SLAM filter
H Deusch, S Reuter, K Dietmayer
IEEE Signal Processing Letters 22 (10), 1561-1565, 2015
1122015
A multiple model PHD approach to tracking of cars under an assumed rectangular shape
K Granström, S Reuter, D Meissner, A Scheel
17th International Conference on Information Fusion (FUSION), 1-8, 2014
1122014
Multiple extended object tracking using Gaussian processes
T Hirscher, A Scheel, S Reuter, K Dietmayer
2016 19th International Conference on Information Fusion (FUSION), 868-875, 2016
1062016
A random finite set approach to multiple lane detection
H Deusch, J Wiest, S Reuter, M Szczot, M Konrad, K Dietmayer
2012 15th International IEEE Conference on Intelligent Transportation …, 2012
922012
Likelihood-based data association for extended object tracking using sampling methods
K Granström, L Svensson, S Reuter, Y Xia, M Fatemi
IEEE Transactions on intelligent vehicles 3 (1), 30-45, 2017
812017
Fusion of laser and radar sensor data with a sequential Monte Carlo Bayesian occupancy filter
D Nuss, T Yuan, G Krehl, M Stuebler, S Reuter, K Dietmayer
2015 IEEE intelligent vehicles symposium (IV), 1074-1081, 2015
812015
A fast implementation of the labeled multi-Bernoulli filter using Gibbs sampling
S Reuter, A Danzer, M Stübler, A Scheel, K Granström
2017 IEEE Intelligent Vehicles Symposium (IV), 765-772, 2017
682017
Multi-object tracking using random finite sets
S Reuter
Universität Ulm, 2014
652014
Pedestrian tracking using random finite sets
S Reuter, K Dietmayer
14th International Conference on Information Fusion, 1-8, 2011
622011
Kalman filter based classifier fusion for affective state recognition
M Glodek, S Reuter, M Schels, K Dietmayer, F Schwenker
Multiple Classifier Systems: 11th International Workshop, MCS 2013, Nanjing …, 2013
562013
Real-time multi-object tracking using random finite sets
S Reuter, B Wilking, J Wiest, M Munz, K Dietmayer
IEEE Transactions on Aerospace and Electronic Systems 49 (4), 2666-2678, 2013
522013
Fusion paradigms in cognitive technical systems for human–computer interaction
M Glodek, F Honold, T Geier, G Krell, F Nothdurft, S Reuter, F Schüssel, ...
Neurocomputing 161, 17-37, 2015
512015
Multi-sensor multi-object tracking of vehicles using high-resolution radars
A Scheel, C Knill, S Reuter, K Dietmayer
2016 IEEE Intelligent Vehicles Symposium (IV), 558-565, 2016
502016
Multi-sensor self-localization based on maximally stable extremal regions
H Deusch, S Reuter, D Nuss, M Fritzsche, K Dietmayer
2014 IEEE Intelligent Vehicles Symposium Proceedings, 555-560, 2014
492014
Multi-camera traffic light recognition using a classifying Labeled Multi-Bernoulli filter
M Bach, S Reuter, K Dietmayer
2017 IEEE Intelligent Vehicles Symposium (IV), 1045-1051, 2017
462017
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