FH-Prof. Priv.-Doz. Dipl.-Ing. Mag. Dr. Matthias Zeppelzauer

  • Forschungsgruppenleiter
    Forschungsgruppe Media Computing
    Institut für Creative\Media/Technologies
  • Department Medien und Digitale Technologien
Arbeitsplatz: A - Campus-Platz 1
M: +43/676/847 228 652


  • Creative Computing (BA)
  • Data Science and Business Analytics (BA)
  • Medientechnik (BA)
  • Data Intelligence (MA)
  • Smart Engineering (BA)


  • Medien und Digitale Technologien
  • Informatik und Security


  • Senior Researcher am Institut für Creative Media Technologies - Fachochschule St. Pölten
  • Bakkalaureatstudium Medieninformatik und Magisterstudium Computergraphik und Bildverarbeitung - Technische Universität Wien
  • Wirtschaftsinformatik - Universität Wien und Technische Universität Wien
  • 2011: Doktoratsstudium im Bereich Audio- und Videoanalyse und Mustererkennung - Technische Universität Wien
  • Forscher am Institut für Softwaretechnik und interaktive Systeme - Technische Universität Wien
  • Forschungsschwerpunkte: inhaltsbasierte Audioanalyse (Bioakustik, Geräuscherkennung, Signalverbesserung), Bild- und Videoanalyse (Videosegmentierung, Objekterkennung, Social Media Analysis, Life Logging), sowie Datamining (Feature Selektion, Clustering)
  • Mitglied in Programmkomitees zahlreicher Fachzeitschriften und Konferenzen im Multimediabereich

Publication Browser


Ausgewählte Publikationen

Tucek, G., Maidhof, C., Vogl, J., Heine, A., Zeppelzauer, M., Steinhoff, M., & Fachner, J. (2022). EEG Hyperscanning and Qualitative Analysis of Moments of Interest in Music Therapy for Stroke Rehabilitation - A Feasibility Study. Brain Science, 12(565).
Baumhauer, T., Schöttele, P., & Zeppelzauer, M. (2022). Machine Unlearning: Linear Filtration for Logit-based Classifiers. Machine Learning.
Slijepcevic, D., Horst, F., Lapuschkin, S., Horsak, B., Raberger, A.-M., Kranzl, A., Samek, W., Breitender, C., Schöllhorn, W., & Zeppelzauer, M. (2022). Explaining Machine Learning Models for Clinical Gait Analysis. ACM Transactions on Computing for Healthcare, 3(2), 14:1-14:27.
Slijepčević, D., Henzl, M., Klausner, L. D., Dam, T., Kieseberg, P., & Zeppelzauer, M. (2021). k‑Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers. Computers & Security, 111, 19.
Bernard, J., Hutter, M., Zeppelzauer, M., Sedlmair, M., & Munzner, T. (2021). ProSeCo: Visual analysis of class separation measures and dataset characteristics. Computers & Graphics, 96, 48–60.
Zielinski, B., Lipinski, M., Juda, M., Zeppelzauer, Matthias, & Dlotko, Pawel. (2021). Persistence Codebooks for Topological Data Analysis. Journal of Artificial Intelligence Review, 54, 1969–2009.
Bernard, Jürgen, Hutter, M., Sedlmair, M., Zeppelzauer, Matthias, & Munzner, Tamara. (2021). A Taxonomy of Property Measures to Unify Active Learning and Human-centered Approaches to Data Labeling. ACM Transactions on Interactive Intelligent Systems (TiiS), 11(3–4), 1–42.
Horsak, B., Slijepcevic, D., Raberger, A.-M., Schwab, C., Worisch, M., & Zeppelzauer, M. (2020). GaitRec, a large-scale ground reaction force dataset of healthy and impaired gait. Scientific Data, 7:143(1), 1–8.
Bernard, Jürgen, Hutter, M., Sedlmair, M., Zeppelzauer, Matthias, & Munzner, Tamara. (2019). A taxonomy of property measures to support the explainability of the interactive data labeling process. ACM Transactions on Interactive Intelligent Systems (TiiS), Submitted.
Despotovic, M., Koch, D., Leiber, S., Döller, M., Sakeena, M., & Zeppelzauer, M. (2019). Prediction and analysis of heating energy demand for detached houses by computer vision. Energy & Buildings, 193, 29–35.
Zielinski, B., Lipinski, Michal, Juda, M., Zeppelzauer, M., & Dlotko, Pawel. (2019). Persistence Bag-of-Words for Topological Data Analysis. Proceedings of the International Joint Conference on Artificial Intelligence 2019, 6.
Koch, D., Despotovic, M., Sakeena, M., Döller, M., & Zeppelzauer, M. (2018). Visual Estimation of Building Condition with Patch-level ConvNets. Proceedings of the 2018 ACM Workshop on Multimedia for Real Estate Tech - RETech"18, 12–17.
Zeppelzauer, M., Zielinski, B., Juda, M., & Seidl, M. (2018). A Study on Topological Descriptors for the Analysis of 3D Surface Texture. Journal on Computer Vision and Image Understanding (CVIU), 167, 74–88.
Zeppelzauer, M., Ringot, A., & Taurer, F. (2018). SoniControl - A Mobile Ultrasonic Firewall. Proceedings of the ACM International Conference on Multimedia. ACM Multimedia Conference, Seoul, South Korea.
Bernard, J., Zeppelzauer, M., Lehmann, M., Müller, M., & Sedlmair, M. (2018). Towards User-Centered Active Learning Algorithms. Computer Graphics Forum, 37, 121–132.
Zeppelzauer, M., Despotovic, M., Sakeena, M., Koch, D., & Döller, M. (2018). Automatic Prediction of Building Age from Photographs. Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR "18), 126–134.
Slijepcevic, D., Zeppelzauer, M., Raberger, A.-M., Schwab, C., Schuller, M., Baca, A., Breiteneder, C., & Horsak, B. (2018). Automatic Classification of Functional Gait Disorders. IEEE Journal of Biomedical and Health Informatics, 5(22), 1653–1661.
Bernard, J., Zeppelzauer, M., Sedlmair, M., & Aigner, W. (2018). VIAL – A Unified Process for Visual-Interactive Labeling. The Visual Computer, 34(1189), 16.
Wagner, M., Slijepcevic, D., Horsak, B., Rind, A., Zeppelzauer, M., & Aigner, W. (2018). KAVAGait: Knowledge-Assisted Visual Analytics for Clinical Gait Analysis. IEEE Transactions on Visualization and Computer Graphics (TVCG), 25(3), 1528–1542.
Bernard, Jürgen, Hutter, M., Zeppelzauer, M., Fellner, D., & Sedlmair, M. (2017). Comparing Visual-Interactive Labeling with Active Learning: An Experimental Study. IEEE Transactions on Visualization and Computer Graphics (TVCG), 24(1).
Zeppelzauer, M., & Schopfhauser, D. (2016). Multimodal classification of events in social media. Image and Vision Computing.
Zaharieva, M., Del Fabro, M., & Zeppelzauer, M. (2015). Cross-Platform Social Event Detection. IEEE Multimedia, 22(3), 14.
Salvador, A., Zeppelzauer, M., Manchón-Vizuente, D., Calafell, A., & Giró-i-Nieto, X. (2015, April 28). Cultural Event Recognition with Visual ConvNets and Temporal Models. Proceedings of the CVPR Workshop ChaLearn Looking at People 2015. Computer Vision and Pattern Recognition (CVPR), Boston, Massachusetts, United States.
Zaharieva, M., Zeppelzauer, M., Del Fabro, M., & Schopfhauser, D. (2015, March 24). Social Event Mining in Large Photo Collections. Proceedings of the International Conference on Multimedia Retrieval. ACM International Conference on Multimedia Retrieval, Shanghai, China.
Zeppelzauer, M. (2013). Automated detection of elephants in wildlife video. EURASIP Journal on Image and Video Processing, 2013(1), 46.
Stöger, A., Heimann, G., Zeppelzauer, M., Ganswindt, A., Hensman, S., & Charlton, B. (2012). Visualizing Sound Emission of Elephant Vocalizations: Evidence for Two Rumble Production Types. Plos One, 7(11:e48907).
Mitrović, D., Zeppelzauer, M., & Breiteneder, C. (2010). Features for Content-Based Audio Retrieval. In Advances in Computers (Vol. 78, pp. 71–150). Burlington: Academic Press.