Team

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

  • Head of
    Media Computing Research Group
    Institute of Creative\Media/Technologies
  • Department of Media and Digital Technologies
Location: D - Heinrich Schneidmadl-Straße 15
M: +43/676/847 228 652

Study programmes

  • Smart Engineering (BA)
  • Media Technology (BA)
  • Data Science and Business Analytics (BA)

Departments

  • Computer Science and Security
  • Media and Digital Technologies

Short profile

  • Since 2013 Senior Researcher at the Media Computing Group, Institute of Creative\Media/Technologies, St. Poelten University of Applied Sciences
  • 2011 – 2015 Postdoctoral researcher at the Interactive Media Systems Group, Vienna University of Technology, Austria
  • 2011 PhD degree in Computer Science from Vienna University of Technology, Austria, Thesis title: Syntactic and Semantic Concepts in Audio-Visual Media, with highest distinction.
  • 2005 – 2011 Predoctoral researcher at the Interactive Media Systems Group, Vienna University of Technology, Austria
  • 2006 Master of Science in Business Informatics from Vienna University of Technology, Austria, with highest distinction.
  • 2005 Master of Science in Computer Graphics & Digital Image Processing from Vienna University of Technology, Austria, with highest distinction.

Selected Publications

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. https://doi.org/10/gh372d
Zielinski, B., Lipinski, M., Juda, M., Zeppelzauer, Matthias, & Dlotko, Pawel. (2020). Persistence Codebooks for Topological Data Analysis. Journal of Artificial Intelligence Review, 41. https://doi.org/0.1007/s10462-020-09897-4
Bernard, Jürgen, Hutter, M., Sedlmair, M., Zeppelzauer, Matthias, & Munzner, Tamara. (2020). A Taxonomy of Property Measures to Unify Active Learning and Human-Centered Approaches To Data Labeling. ACM Transactions on Interactive Intelligent Systems (TiiS), to appear.
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/fsxn
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. https://doi.org/10/ghpp7z
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/ghppzn
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/ghz24w
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/ghpp2m
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/gdw79h
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/gh377f
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/gd5hr3
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/ghpp2h
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/ghpp2k
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/gcqb3r
Zeppelzauer, M., & Schopfhauser, D. (2016). Multimodal classification of events in social media. Image and Vision Computing. https://doi.org/10/ghpp2q
Zaharieva, M., Del Fabro, M., & Zeppelzauer, M. (2015). Cross-Platform Social Event Detection. IEEE Multimedia, 22(3), 14. https://doi.org/10/gh3773
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/f3snb6
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

Projects