@article{zeppelzauer_study_2016, title = {A {Study} on {Topological} {Descriptors} for the {Analysis} of {3D} {Surface} {Texture}}, abstract = {Methods from computational topology are becoming more and more popular in computer vision and have shown to improve the state-of-the-art in several tasks. In this paper, we investigate the applicability of topological descriptors in the context of 3D surface analysis for the classification of different surface textures. We present a comprehensive study on topological descriptors, investigate their robustness and expressiveness and compare them with state-of-the-art methods. Results show that class-specific information is reflected well in topological descriptors. The investigated descriptors can directly compete with non-topological descriptors and capture orthogonal information. Moreover they improve the state-of-the-art in combination with non-topological descriptors.}, journal = {Journal on Computer and System Sciences}, author = {Zeppelzauer, Matthias and Zielinski, Bartosz and Juda, Mateusz and Seidl, Markus}, year = {2016}, note = {Projekt: PITOTI 3D}, keywords = {2016, 3D surface classification, Center for Artificial Intelligence, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Media Computing Group, Publikationstyp Schriftpublikation, SP, Surface texture analysis, Wiss. Beitrag, best, best-lbseidl, peer-reviewed, persistence diagram, persistence image, persistent homology, surface representation, surface topology analysis, ⛔ No DOI found}, pages = {60}, } @inproceedings{seidl_multi-touch_2011, address = {Prato, Italy}, title = {Multi-touch {Rocks}: {Playing} with {Tangible} {Virtual} {Heritage} in the {Museum} - {First} {User} {Tests}}, booktitle = {{VAST11}: {The} 12th {International} {Symposium} on {Virtual} {Reality}, {Archaeology} and {Cultural} {Heritage} - {Short} and {Project} {Papers}}, publisher = {Eurographics Association}, author = {Seidl, Markus and Judmaier, Peter and Baker, Frederick and Chippindale, Christopher and Egger, Ursula and Jax, Nadine and Weis, Christoph and Grubinger, Martin and Seidl, Georg}, year = {2011}, note = {Projekt: FORSCH06 Projekt: PITOTI 3D}, keywords = {Center for Artificial Intelligence, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Wiss. Beitrag, peer-reviewed, ⛔ No DOI found}, } @article{zeppelzauer_study_2018, title = {A {Study} on {Topological} {Descriptors} for the {Analysis} of {3D} {Surface} {Texture}}, volume = {167}, issn = {1077-3142}, url = {https://arxiv.org/pdf/1710.10662}, doi = {10/ghpp2h}, abstract = {Methods from computational topology are becoming more and more popular in computer vision and have shown to improve the state-of-the-art in several tasks. In this paper, we investigate the applicability of topological descriptors in the context of 3D surface analysis for the classification of different surface textures. We present a comprehensive study on topological descriptors, investigate their robustness and expressiveness and compare them with state-of-the-art methods. Results show that class-specific information is reflected well in topological descriptors. The investigated descriptors can directly compete with non-topological descriptors and capture orthogonal information. Moreover they improve the state-of-the-art in combination with non-topological descriptors.}, journal = {Journal on Computer Vision and Image Understanding (CVIU)}, author = {Zeppelzauer, Matthias and Zielinski, Bartosz and Juda, Mateusz and Seidl, Markus}, year = {2018}, note = {Projekt: PITOTI 3D}, keywords = {3D surface classification, Center for Artificial Intelligence, Computer Vision, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Surface texture analysis, Visual Computing, Wiss. Beitrag, best, best-lbseidl, best-mzeppelzauer, peer-reviewed, persistence diagram, persistence image, persistent homology, surface representation, surface topology analysis}, pages = {74 -- 88}, } @inproceedings{seidl_automated_2012, address = {New York, NY, USA}, series = {{ICVGIP} '12}, title = {Automated petroglyph image segmentation with interactive classifier fusion}, isbn = {978-1-4503-1660-6}, url = {http://doi.acm.org/10.1145/2425333.2425399}, doi = {10/gh372j}, booktitle = {Proceedings of the {Eighth} {Indian} {Conference} on {Computer} {Vision}, {Graphics} and {Image} {Processing}}, publisher = {ACM}, author = {Seidl, Markus and Breiteneder, Christian}, year = {2012}, note = {Projekt: FORSCH08 Projekt: PITOTI 3D}, keywords = {Center for Artificial Intelligence, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Pattern recognition, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Wiss. Beitrag, best, best-lbseidl, experimental study, image features, image segmentation, peer-reviewed, petroglyphs, pixel classification, rock art}, pages = {66:1--66:8}, } @book{seidl_forum_2014, address = {Glueckstadt}, title = {Forum {Medientechnik} – {Next} {Generation}, {New} {Ideas} {Beitraege} der {Tagung} 2013 an der {Fachhochschule} {St}. {Poelten}}, isbn = {978-3-86488-058-2 3-86488-058-0}, publisher = {Huelsbusch, W}, author = {Seidl, Markus and Schmiedl, Grischa and Kastel, Thiemo}, year = {2014}, keywords = {Center for Artificial Intelligence, Creative Industries, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, peer-reviewed}, }