dr.ir. L.J. Spreeuwers (Luuk)

Associate Professor
EEMCS-CS-DMB
Zilverling 4067
l.j.spreeuwers@utwente.nl
+31534893368
Business card

Dr. Luuk Spreeuwers studied Electrical Engineering at the University of Twente, Netherlands. In 1992 he obtained his PhD from the University of Twente. The title of his PhD-thesis is: Image Filtering with Neural Networks: Applications and Performance Evaluation. Subsequently Luuk Spreeuwers worked at the International Institute for Aerospace and Earth Sciences (ITC) in Enschede, Netherlands, the University of Twente in a SION project on 3-D image analysis of aerial image sequences and in Budapest at the Hungarian Academy of Sciences in a 3-D textures ERCIM project. From 1999-2005 Luuk Spreeuwers worked on 3-D modelling and segmentation of the human heart in MRI at the Image Sciences Institute of the University Medical Centre in Utrecht, the Netherlands. Currently, he is an Associate Professor at the Data Management and Biometrics Group of the Department of EEMCS of the University of Twente, Netherlands where he is the leader of the biometrics sub-group. In addition, he is the programme mentor of the Computer Vision and Biometrics Master Specialisation and is actively involved in teaching Bachelor's and Master's courses and president of the EE Programme Committee. He was nominated 6 times for the EE Educational award and won the prize in 2018. Luuk Spreeuwers has published over 100 papers in international conferences and journals. In 2015 he published a paper on 3D face recognition where he claimed the world's best performance on a recognised benchmark in 3D face recognition. In 2017 he won the best paper award at the BIOSIG conference with the paper titled: "De-Duplication using automated Face Recognition. An accurate mathematical Model and all Babies are equally cute". He was and is involved in numerous national and European projects among which 3DFace, SOTAMD and currently iMARS. His expertise involves digital image processing and analysis, medical image analysis, biometrics and pattern recognition in general.

Expertise

  • Computer Science

    • Face Recognition
    • Biometrics
    • Morphing
    • Recognition System
    • Forensics
    • Attack
    • Database
    • Detection

Organisations

Publications

2024
Vulnerability of face recognition to morphing: a latent space perspective. University of Twente. Kelly, U. M.https://doi.org/10.3990/1.9789036561396Language-Based Augmentation to Address Shortcut Learning in Object-Goal NavigationIn Proceedings - 2023 7th IEEE International Conference on Robotic Computing, IRC 2023 (pp. 1-8). IEEE. Hoftijzer, D., Burghouts, G. & Spreeuwers, L.https://doi.org/10.1109/IRC59093.2023.00007Language-Based Augmentation to Address Shortcut Learning in Object Goal Navigation. Hoftijzer, D., Burghouts, G. & Spreeuwers, L.Robust partial face recognition using multi-label attributes, 377-392. Sang, G., Zeng, D., Yan, C., Veldhuis, R. & Spreeuwers, L.https://doi.org/10.3233/IDA-227309The Impact of Illumination on Finger Vascular Pattern Recognition, Article 4413655. Normakristagaluh, P., Laanstra, G. J., Spreeuwers, L. J. & Veldhuis, R. N. J.https://doi.org/10.1049/2024/4413655
2023
Mathematical Camera Array Optimization for Face 3D Modeling Application, Article 9776. Alsadik, B., Spreeuwers, L., Dadrass Javan, F. & Manterola, N.https://doi.org/10.3390/s23249776Worst-Case Morphs Using Wasserstein ALI and Improved MIPGAN, Article 9353816. Kelly, U. M., Nauta, M., Liu, L., Spreeuwers, L. J. & Veldhuis, R. N. J.https://doi.org/10.1049/2023/9353816Deep neural networks for explainable feature extraction in orchid identification, 26270-26285. Apriyanti, D. H., Spreeuwers, L. J. & Lucas, P. J. F.https://doi.org/10.1007/s10489-023-04880-2The Impact of Eyebrows Region on Deep Face RecognitionIn 2023 10th International Conference on Computer, Control, Informatics and its Applications: Exploring the Power of Data: Leveraging Information to Drive Digital Innovation, IC3INA 2023 (pp. 319-323). IEEE. Lestriandoko, N. H., Spreeuwers, L. & Veldhuis, R.https://doi.org/10.1109/IC3INA60834.2023.10285734Worst-Case Morphs using Wasserstein ALI and Improved MIPGAN. ArXiv.org. Kelly, U. M., Nauta, M., Liu, L., Spreeuwers, L. J. & Veldhuis, R. N. J.https://doi.org/10.48550/arXiv.2310.08371

Research profiles

Courses academic year 2023/2024

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses academic year 2022/2023

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