@article{zeppelzauer_interactive_2016, title = {Interactive {3D} {Segmentation} of {Rock}-{Art} by {Enhanced} {Depth} {Maps} and {Gradient} {Preserving} {Regularization}}, volume = {9}, issn = {1556-4673}, url = {https://publik.tuwien.ac.at/files/publik_258520.pdf}, doi = {10/ghpp2n}, number = {4}, journal = {ACM Journal on Computing and Cultural Heritage}, author = {Zeppelzauer, Matthias and Poier, Georg and Seidl, Markus and Reinbacher, Christian and Schulter, Samuel, Christian and Breiteneder, C. and Bischof, Horst}, month = jul, year = {2016}, note = {Article 19 Projekt: PITOTI 3D}, keywords = {Center for Artificial Intelligence, Computer Vision, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Publikationstyp Schriftpublikation, Wiss. Beitrag, best, peer-reviewed}, pages = {19:1--19:30}, } @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}, } @misc{zeppelzauer_novel_2015, address = {Boston, Massachusetts, United States}, title = {A {Novel} {Annotation} {Tool} for {Complex} {Petroglyph} {Shapes}}, url = {http://mc.fhstp.ac.at/content/novel_annotation_tool_complex_petroglyph_shapes}, abstract = {We present a novel semi-automatic annotation tool for the construction of large real-world shape datasets. The tool enables the collaborative semi-automatic segmentation and annotation of shapes. Shapes are stored together with their annotations in a database and can be retrieved efficiently to construct custom shape datasets. The resulting datasets should stimulte further reasearch in the domain of shape recognition and matching.}, author = {Zeppelzauer, Matthias and Wieser, Ewald and Seidl, Markus}, month = jun, year = {2015}, note = {Projekt: PITOTI 3D}, keywords = {2015, Center for Artificial Intelligence, Computer Vision, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Poster, Schriftpublikation, Wiss. Beitrag}, } @inproceedings{zeppelzauer_novel_2015-1, address = {Boston, MA, USA}, title = {A {Novel} {Annotation} {Tool} for {Complex} {Petroglyph} {Shapes}}, abstract = {We present a novel semi-automatic annotation tool for the construction of large real-world shape datasets. The tool enables the collaborative semi-automatic segmentation and annotation of shapes. Shapes are stored together with their annotations in a database and can be retrieved efficiently to construct custom shape datasets. The resulting datasets should stimulte further reasearch in the domain of shape recognition and matching.}, booktitle = {The {Future} of {Datasets} in {Vision} {Workshop} (in conjunction with {CVPR} 2015)}, author = {Zeppelzauer, Matthias and Wieser, Ewald and Seidl, Markus}, year = {2015}, note = {Projekt: PITOTI 3D}, keywords = {2015, Center for Artificial Intelligence, Creative Industries, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Vortrag, Wiss. Beitrag, best, peer-reviewed, poster, ⛔ No DOI found}, } @inproceedings{seidl_detection_2011, address = {Prato, Italy}, title = {Detection and {Classification} of {Petroglyphs} in {Gigapixel} {Images} –{Preliminary} {Results}}, booktitle = {The 12th {International} {Symposium} on {Virtual} {Reality}, {Archaeology} and {Cultural} {Heritage} {VAST11} - {Short} and {Project} {Papers}}, publisher = {Eurographics Association}, author = {Seidl, Markus and Breiteneder, Christian}, year = {2011}, 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, peer-reviewed, ⛔ No DOI found}, } @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}, } @inproceedings{zeppelzauer_efficient_2015, address = {Quebec, Canada}, title = {Efficient {Image}-{Space} {Extraction} and {Representation} of {3D} {Surface} {Topography}}, url = {http://arxiv.org/pdf/1504.08308v3.pdf}, doi = {10/ghp4kc}, booktitle = {Conference {Proceedings} of {ICIP} - {IEEE} {International} {Conference} on {Image} {Processing} 2015}, publisher = {IEEE}, author = {Zeppelzauer, Matthias and Seidl, Markus}, year = {2015}, note = {Projekt: PITOTI 3D}, keywords = {2015, 3D descriptors, 3D surface analysis, Center for Artificial Intelligence, Computer Vision, Creative Industries, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Image processing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Surface microstructure, Topography classification, Vortrag, Wiss. Beitrag, best-lbseidl, peer-reviewed}, pages = {2845--2849}, } @article{wieser_study_2016, title = {A {Study} on {Skeletonization} of {Complex} {Petroglyph} {Shapes}}, issn = {1573-7721}, url = {http://link.springer.com/article/10.1007/s11042-016-3395-1}, doi = {10/ghpp2r}, abstract = {In this paper, we present a study on skeletonization of real-world shape data. The data stem from the cultural heritage domain and represent contact tracings of prehistoric petroglyphs. Automated analysis can support the work of archeologists on the investigation and categorization of petroglyphs. One strategy to describe petroglyph shapes is skeleton-based. The skeletonization of petroglyphs is challenging since their shapes are complex, contain numerous holes and are often incomplete or disconnected. Thus they pose an interesting testbed for skeletonization. We present a large real-world dataset consisting of more than 1100 petroglyph shapes. We investigate their properties and requirements for the purpose of skeletonization, and evaluate the applicability of state-of-the-art skeletonization and skeleton pruning algorithms on this type of data. Experiments show that pre-processing of the shapes is crucial to obtain robust skeletons. We propose an adaptive pre-processing method for petroglyph shapes and improve several state-of-the-art skeletonization algorithms to make them suitable for the complex material. Evaluations on our dataset show that 79.8 \% of all shapes can be improved by the proposed pre-processing techniques and are thus better suited for subsequent skeletonization. Furthermore we observe that a thinning of the shapes produces robust skeletons for 83.5 \% of our shapes and outperforms more sophisticated skeletonization techniques.}, journal = {Multimedia Tools and Applications (Springer)}, author = {Wieser, Ewald and Seidl, Markus and Zeppelzauer, Matthias}, year = {2016}, note = {Projekt: PITOTI 3D}, keywords = {2016, Center for Artificial Intelligence, Computer Vision, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Pattern recognition, Publikationstyp Schriftpublikation, Real-world shape data, Shape pre-processing, Skeletionization, Skeletonization, Wiss. Beitrag, best, peer-reviewed, petroglyphs}, pages = {1--19}, } @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{zeppelzauer_topological_2016, address = {Marseilles, France}, title = {Topological descriptors for {3D} surface analysis}, volume = {9667}, doi = {10/gh377g}, booktitle = {In {Proceedings} of 6th {International} {Workshop} on {Computational} {Topology} in {Image} {Context}}, publisher = {Springer}, author = {Zeppelzauer, Matthias and Zielinski, Bartosz and Juda, Mateusz and Seidl, Markus}, year = {2016}, note = {Projekt: PITOTI 3D}, keywords = {2016, Center for Artificial Intelligence, Computer Vision, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Wiss. Beitrag, peer-reviewed}, pages = {77--87}, } @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}, } @article{seidl_automated_2015, title = {Automated classification of petroglyphs}, issn = {2212-0548}, url = {http://www.sciencedirect.com/science/article/pii/S2212054815000090}, doi = {10/gd6csz}, abstract = {Abstract In this paper, we address the problem of automated petroglyph classification in a large real-world dataset. The dataset which contains more than 1000 petroglyphs is based on tracings from the \{UNESCO\} world heritage site Valcamonica, Italy and is expert-classified into two parallel typologies. For automated classifications of petroglyphs we utilise a combination of existing shape descriptors and a recently developed graph-based petroglyph descriptor. We achieve good classification results. We evaluate how the results can be incorporated into the daily work of archaeologists. We demonstrate that our tools can clearly enhance the process of manual classification.}, number = {0}, journal = {Digital Applications in Archaeology and Cultural Heritage}, author = {Seidl, Markus and Wieser, Ewald and Alexander, Craig}, year = {2015}, note = {Projekt: PITOTI 3D}, keywords = {2015, Creative Industries, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Wiss. Beitrag, best, peer-reviewed, visual computing}, pages = {--}, } @inproceedings{zeppelzauer_interactive_2015, address = {Granada, Spain}, title = {Interactive {Segmentation} of {Rock}-{Art} in {High}-{Resolution} {3D} {Reconstructions}}, booktitle = {Conference {Proceedings} of {Digital} {Heritage} 2015 {Full} {Papers}}, author = {Zeppelzauer, Matthias and Poier, Georg and Seidl, Markus and Reinbacher, Christian and Breiteneder, Christian and Bischof, Horst}, month = oct, year = {2015}, note = {Projekt: PITOTI 3D}, keywords = {2015, Center for Artificial Intelligence, Computer Vision, Creative Industries, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Publikationstyp Schriftpublikation, Vortrag, Wiss. Beitrag, best, peer-reviewed}, } @inproceedings{agapito_graph-based_2015, series = {Lecture {Notes} in {Computer} {Science}}, title = {Graph-{Based} {Shape} {Similarity} of {Petroglyphs}}, volume = {8925}, isbn = {978-3-319-16177-8}, url = {http://dx.doi.org/10.1007/978-3-319-16178-5_9}, language = {English}, booktitle = {Computer {Vision} - {ECCV} 2014 {Workshops}}, publisher = {Springer International Publishing}, author = {Seidl, Markus and Wieser, Ewald and Zeppelzauer, Matthias and Pinz, Axel and Breiteneder, Christian}, editor = {Agapito, Lourdes and Bronstein, Michael M. and Rother, Carsten}, year = {2015}, note = {Projekt: PITOTI 3D}, keywords = {2015, Center for Artificial Intelligence, Computer Vision, Creative Industries, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Graph edit distance, Graph embedding, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Petroglyph similarity, Publikationstyp Schriftpublikation, Shape similarity, Vortrag, Wiss. Beitrag, best, best-lbseidl, graph matching, peer-reviewed, visual computing}, pages = {133--148}, } @misc{seidl_digitally_2017, address = {Graz, Austria}, type = {Invited talk}, title = {Digitally {Enhancing} {Museum} {Experience} \& {Understanding} of {Archeological} {Artefacts}}, abstract = {Digital artefacts can enhance the museum experience and computational analysis can improve the understanding of archeological artefacts. The first aspect targets the general public, whilst the latter mainly targets domain experts. In my presentation I will include both aspects by showing on one hand a strand of multi-touch tabletop applications for museums developed by our group and on the other hand the usage of computer vision techniques for the computational analysis of petroglyphs. The digital tabletop applications have mostly been designed and developed for young target groups and were exhibited e.g. in the Prunksaal of the Austrian National Library, the Triennale Design Museum in Milano and the Museum of Archaeology and Anthropology at Cambridge University. Currently we are investigating the inclusion of the visitor´s own devices in the digital ecosystems of museums. In the second part I will present methods that aim at supporting the classic documentation pipeline for rock art. I will show approaches for surface segmentation, shape classification and pecking style analysis of petroglyphs based on 2D and 3D images thereof.}, author = {Seidl, Markus}, month = sep, year = {2017}, note = {Projekt: PITOTI 3D Projekt: MEETeUX}, keywords = {2017, Department Medien und Digitale Technologien, Forschungsgruppe Media Computing, ICMT, Institut für Creative Media Technologies, Publikationstyp Präsentation}, } @phdthesis{seidl_computational_2016, address = {Vienna}, type = {{PhD} {Thesis}}, title = {Computational {Analysis} of {Petroglyphs}}, url = {http://ment.org/files/Dissertation_Markus_Seidl_20160819_final_compressed.pdf}, abstract = {Numerous petroglyphs have been pecked, scratched and carved into rock surfaces in the northern Italian valley Valcamonica. The classic documentation work carried out by archaeologists is a massively time-consuming process. The rising availability of digital images and 3D scans of petroglyphs facilitates digital workflows which can improve the documentation process. In this thesis, we aim at supporting the classic documentation pipeline for petroglyphs. The first step of the pipeline is the determination of the boundaries and spatial locations of petroglyphs on a rock surface. This is usually done by time-consuming manual contact tracing. Then, the found figures are classified according to their shapes and pecking styles. The large number of petroglyphs (Valcamonica contains up to 300.000 figures) demands large efforts for manual classification. The investigation of pecking styles is often impossible based on the contact tracings and thus requires researchers to return to the rocks frequently. Following the classic documentation pipeline for petroglyphs, we propose and evaluate novel methods. To determine the positions and shapes of petroglyphs on a rock panel we approach segmentation of 2D and 3D petroglyph images in pecked regions and natural rock surface. Furthermore, we use 3D scans to investigate the similarity of pecking styles, i.e. the shape, size, depth and spatial distribution of the peck marks a figure consists of. Finally, we develop a petroglyph shape descriptor which allows the classification of petroglyphs. Our tasks are challenging. The figures have been pecked over thousands of years. The rocks are subject to weathering and abrasion. Therefore, the visual and tactile appearance of the petroglyphs varies greatly. Figures have often been superimposed over existing figures. Consequently, many merged and partial figures exist. Contrary to previous work by others, we show that the segmentation of 2D images of rock surfaces is feasible. The employment of illumination-independent high-resolution 3D data of the surfaces’ micro-topographies clearly improves results. We facilitate the investigation of pecking styles by modeling their similarity with 3D surface descriptors. The shape classification of a dataset containing more than thousand petroglyphs yields very good results with a combination of skeleton-, boundary-, and region-based shape descriptors. Our results can be useful for rock art researchers. Furthermore, we suggest how they can be applied in other domains.}, school = {Vienna University of Technology}, author = {Seidl, Markus}, year = {2016}, note = {Projekt: PITOTI 3D}, keywords = {2016, Computer Vision, Computing and Cultural Heritage, Department Medien und Digitale Technologien, Department Technologie, Extern, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Segmentation, Shape descriptors, Surface Classification, Surface Description, Valcamonica, Wiss. Beitrag, petroglyphs, pixel classification}, } @misc{seidl_digital_2014, address = {Cambridge University. Department of Archaeology}, title = {“{Digital} {Tracing}”, {Classification} and {Analysis} of {2D} and {3D} {Recordings} of {Petroglyphs}}, abstract = {Classic recording methods for rock art are time consuming and reliant on good weather and the appropriate season. The possibilities of digital photography and 3D image acquisition allow us to do the “tracing” digitally. Subsequent processing and automated analysis of the images obtained may support further research by the archaeologist. We demonstrated promising results for “automated digital tracing” of petroglyph images (i.e. discrimination between man-made peck marks and the natural rock surface) on high-resolution 2D digital pictures in 2012. In the currently running 3D-Pitoti project, we aim to achieve (semi-) “automated digital tracing” of 3D surface scans, the in-depth morphometrical analysis of peck marks as well as the automated classification of petroglyph shapes. We will show both results of the 2D “digital tracing” and preliminary results of our work in the 3D-Pitoti project.}, author = {Seidl, Markus and Wieser, Ewald and Alexander, Craig}, month = may, year = {2014}, note = {Projekt: PITOTI 3D}, keywords = {2014, Department Technologie, Institut für Creative Media Technologies, Publikationstyp Präsentation}, } @misc{seidl_intelligent_2015, address = {The Cyprus Institute}, type = {Kolloquium}, title = {Intelligent {Processing} of {High} {Resolution} {3D} {Scans} of {Rock} {Art}}, author = {Seidl, Markus}, month = jan, year = {2015}, note = {Projekt: PITOTI 3D}, keywords = {2015, Department Technologie, Institut für Creative Media Technologies, Publikationstyp Präsentation}, }