Team

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

  • Forschungsgruppenleiter
    Forschungsgruppe Media Computing
  • Department Medien und Digitale Technologien
Arbeitsplatz: D - Heinrich Schneidmadl-Straße 15
T: +43/2742/313 228 652

Studiengänge

  • Medientechnik (BA)
  • Smart Engineering (BA)
  • Data Science and Business Analytics (BA)

Departments

  • Medien und Digitale Technologien
  • Informatik und Security

Kurzprofil

  • 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

Ausgewählte Publikationen

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(1), 143. https://doi.org/10.1038/s41597-020-0481-z
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.
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. http://arxiv.org/abs/1802.04852
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. https://doi.org/10.1016/j.enbuild.2019.03.036
Bernard, J., Zeppelzauer, M., Sedlmair, M., & Aigner, W. (2018). VIAL – A Unified Process for Visual-Interactive Labeling. The Visual Computer, 34(1189), 16. https://doi.org/10.1007/s00371-018-1500-3
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. https://doi.org/10.1145/3240508.3241393
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. https://doi.org/10.1109/TVCG.2017.2785271
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. https://doi.org/10.1109/JBHI.2017.2785682
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. https://doi.org/10.1145/3210499.3210526
Bernard, J., Zeppelzauer, M., Lehmann, M., Müller, M., & Sedlmair, M. (2018). Towards User-Centered Active Learning Algorithms. Computer Graphics Forum, 37, 121–132. https://doi.org/10.1111/cgf.13406
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. https://doi.org/10.1145/3206025.3206060
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. https://doi.org/10.1016/j.cviu.2017.10.012
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). https://doi.org/10.1109/TVCG.2017.2744818
Zeppelzauer, M., & Schopfhauser, D. (2016). Multimodal classification of events in social media. Image and Vision Computing. https://doi.org/http://dx.doi.org/10.1016/j.imavis.2015.12.004
Zaharieva, M., Del Fabro, M., & Zeppelzauer, M. (2015). Cross-Platform Social Event Detection. IEEE Multimedia, 22(3), 14. https://doi.org/10.1109/MMUL.2015.31
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. http://arxiv.org/abs/1504.06567
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. https://doi.org/10.1186/1687-5281-2013-46
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). http://dx.plos.org/10.1371/journal.pone.0048907
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. http://www.sciencedirect.com/science/article/pii/S0065245810780037

Projekte

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