+43/2742/313 228 - 652
Mag. Dipl.Ing. Dr.

Matthias Zeppelzauer is data science and pattern recognition researcher and works as a senior researcher at the Institute of Creative Media Technologies at St. Poelten University of Applied Sciences, since 2013.

From 2011 to 2015, he worked as a postdoctoral researcher at the Interactive Media Systems Group at the Vienna University of Technology in the areas of content-based audio and visual retrieval, computer vision, and machine learning. He graduated with Master of Sciences at Vienna University of Technology in Computer Science and Business Informatics in 2005 and 2006, respectively, and holds a PhD in Computer Science from the Vienna University of Technology. Matthias Zeppelzauer is involved in the acquisition and execution of a numerous basic and applied research projects at national and international levels. He is a lecturer for undergraduate- and graduate programs with an emphasis on signal processing and content-based retrieval. Matthias Zeppelzauer received several performance scholarships from the Vienna University of Technology and was awarded by the Austrian Computer Society for outstanding achievements in the area of pattern recognition.

Research Interests: pattern recognition · computer vision · machine learning · deep learning · data mining · multimodal retrieval· social media analysis


Recent Publications

Poier, G., M. Seidl, M. Zeppelzauer, C. Reinbacher, M. Schaich, G. Bellandi, A. Marretta, and H. Bischof, "The 3D-Pitoti Dataset: A Dataset for high-resolution 3D Surface Segmentation", Content Based Multimedia Indexing, Special Session on Multimedia for Cultural Heritage, Florence, pp. 8, 06/2017.
Bernard, J., C. Ritter, D. Sessler, M. Zeppelzauer, J. Kohlhammer, and D. Fellner, "Visual-Interactive Similarity Search for Complex Objects by Example of Soccer Player Analysis", In Proceedings of 12th International Conference on Information Visualization, Theory and Applications, 2017.
Poier, G., M. Seidl, M. Zeppelzauer, C. Reinbacher, M. Schaich, G. Bellandi, A. Marretta, and H. Bischof, "PetroSurf3D - A high-resolution 3D Dataset of Rock Art for Surface Segmentation", CoRR, vol. abs/1610.01944: arxiv.org, 11/2016.
Zeppelzauer, M., B. Zielinski, M. Juda, and M. Seidl, "A Study on Topological Descriptors for the Analysis of 3D Surface Texture", Submitted to: Journal on Computer and System Sciences, pp. 60, 2016.
Zeppelzauer, M., G. Poier, M. Seidl, C. Reinbacher, S. Schulter, C. Breiteneder, and H. Bischof, "Interactive 3D Segmentation of Rock-Art by Enhanced Depth Maps and Gradient Preserving Regularization", ACM Journal on Computing and Cultural Heritage, vol. 9, 4, Article 19, 08/2016.

Press articles