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Prof. Dr. Jan Salmen

Dr.-Ing., Dipl.-Inf.
Faculty of Information, Media and Electrical Engineering

Institute of Media and Imaging Technology

Prof. Dr. Jan Salmen

Campus Deutz
Betzdorfer Straße 2
50679 Köln
Room ZW 10-4 Mailing address


  • Phone: +49 221-8275-4432

Office hours

By arrangement. You are welcome to join one of my ILU courses and book an appointment through the calendar there

Teaching disciplines

Research fields

  • Real-time computer vision
  • Machine Learning in practical applications
  • Sports Analytics
  • Evolutionary Optimization of Wavelet Feature Sets for Real-Time Pedestrian Classification
    Salmen, J. ; Suttorp, T. ; Edelbrunner, J. ; Igel, C., 2007, Publisher: Proceedings of the IEEE Conference on Hybrid Intelligent Systems, S. 222–227
  • Real-Time Stereo Vision: Making more out of Dynamic Programming
    Salmen, J. ; Schlipsing, M. ; Edelbrunner, J. ; Hegemann, S. ; Lueke, S., 2009, Publisher: Proceedings of the International Conference on Computer Analysis of Images and Patterns, S. 1096–1103
  • Efficient Update of the Covariance Matrix Inverse in Iterated Linear Discriminant Analysis
    Salmen, J. ; Schlipsing, M. ; Igel, C., 2010, Publisher: Pattern Recognition Letters 31, S. 1903–1907
  • Real-Time Estimation of Optical Flow based on Optimized Haar Wavelet Features
    Salmen, J. ; Caup, L. ; Igel, C., 2011, Publisher: Proceedings of the International Conference on Evolutionary Multi-Criterion Optimization, S. 448–461
  • Video-Based Roll Angle Estimation for Two-Wheeled Vehicles
    Schlipsing, M. ; Schepanek, J. ; Salmen, J., 2011, Publisher: Proceedings of the IEEE Intelligent Vehicles Symposium, S. 876–881
  • The German Traffic Sign Recognition Benchmark: A multi-class classification competition
    Stallkamp, J. ; Schlipsing, M. ; Salmen, J. ; Igel, C., 2011, Publisher: Proceedings of the IEEE International Joint Conference on Neural Networks, S. 1453–146
  • Man vs. Computer: Benchmarking Machine Learning Algorithms for Traffic Sign Recognition
    Stallkamp, J. ; Schlipsing, M. ; Salmen, J. ; Igel, C., 2012, Publisher: Neural Networks 32, S. 323–332
  • Introduction to the Special Issue on Machine Learning for Traffic Sign Recognition
    Stallkamp, J. ; Schlipsing, M. ; Salmen, J. ; Igel, C., 2012, Publisher: IEEE Transactions on Intelligent Transportation Systems 13(4), S. 1481–1483
  • Roll Angle Estimation for Motorcycles: Comparing Video and Inertial Sensor Approaches
    Schlipsing, M. ; Salmen, J. ; Lattke, B. ; Schröter, K. ; Winner, H., 2012, Publisher: Proceedings of the IEEE Intelligent Vehicles Symposium, S. 500–505
  • Google Street View Images Support the Development of Vision-Based Driver Assistance Systems
    Salmen, J. ; Houben, S. ; Schlipsing, M., 2012, Publisher: Proceedings of the IEEE Intelligent Vehicles Symposium, S. 891–895
  • Real-Time Stereo Vision: Optimizing Semi-Global Matching
    Michael, M. ; Salmen, J. ; Stallkamp, J. ; Schlipsing, M., 2013, Publisher: Proceedings of the IEEE Intelligent Vehicles Symposium, S. 1197–1202
  • Video-Based Trailer Articulation Estimation
    Caup, L. ; Salmen, J. ; Muharemovic, I. ; Houben, S, 2013, Publisher: Proceedings of the IEEE Intelligent Vehicles Symposium, S. 1179– 1184
  • Detection of traffic signs in real-world images: The German Traffic Sign Detection Benchmark
    Houben, S. ; Stallkamp, J. ; Salmen, J. ; Schlipsing, M. ; Igel, C., 2013, Publisher: Proceedings of the IEEE International Joint Conference on Neural Networks, S. 1–8
  • Towards Autonomous Driving in a Parking Garage: Vehicle Localization and Tracking Using Environment-embedded Lidar Sensors
    Ibisch, A. ; Stümper, S. ; Altinger, H. ; Neuhausen, M. ; Tschentscher, M. ; Schlipsing, M. ; Salmen, J. ; Knoll, A., 2013, Publisher: Proceedings of the IEEE Intelligent Vehicles Symposium, S. 829–834
  • Comparing Image Features and Machine Learning Algorithms for Real-time Parking Space Classification
    Tschentscher, M. ; Neuhausen, M. ; Koch, C. ; König, M. ; Salmen, J. ; Schlipsing, M., 2013, Publisher: Proceedings of the ASCE Conference on Computing in Civil Engineering, S. 363–370
  • Echtzeit-Videoanalyse im Fußball – Ein Live-System zum Spieler-Tracking
    Schlipsing, M. ; Salmen, J. ; Igel, C., 2013, Publisher: Künstliche Intelligenz 27(3), S. 235–240
  • Adaptive Pattern Recognition in Real-time Video-based Soccer Analysis
    Schlipsing, M. ; Salmen, J. ; Tschentscher, M. ; Igel, C., 2014, Publisher: Journal of Real-Time Image Processing, S. 1–17
  • Scalable Real-time Parking Lot Classification: An Evaluation of Image Features and Supervised Learning Algorithms
    Tschentscher, M. ; Koch, C. ; König, M. ; Salmen, J. ; Schlipsing, M., 2015, Publisher: Proceedings of the IEEE International Joint Conference on Neural Networks, S. 1–8
  • Metabolic Power and Energy Expenditure in the German Bundesliga
    Venzke, J. ; Weber, H. ; Schlipsing, M. ; Salmen, J. ; Platen, P., 2018, Publisher: Proceedings of the 23rd Annual Congress of the European College of Sport Science
1991–2000 Gymnasium: Hildegardisschule Bochum
2000–2001 Zivildienst: Jugendherberge Essen-Werden
2001–2006 Studium: Kerninformatik mit Nebenfach VWL an der TU Dortmund
2006–2013 Wissenschaftlicher Mitarbeiter am Institut für Neuroinformatik der Ruhr-Universität Bochum
Leitung der Arbeitsgruppe "Echtzeitfähige Bildverarbeitung" ab 2008. Promotion 2013 zum Thema "Eine Systemarchitektur für effiziente videobasierte Fahrerassistenzsysteme"
2013–2018 Lehrbeauftragter Hochschule Ruhr West, Bottrop
2013–2014 Existenzgründer-Stipendium EXIST des BMWi
2014–2022 Geschäftsführender Gesellschafter ATHLENS GmbH, Bochum
since 07/2022 Professur für "Computer Vision and Machine Learning"

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