DSpace Repository :: Browsing by Author "Lengauer, Stefan"

Browsing by Author "Lengauer, Stefan"

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A Benchmark Dataset for Repetitive Pattern Recognition on Textured 3D Surfaces
(The Eurographics Association and John Wiley & Sons Ltd., 2021) Lengauer, Stefan; Sipiran, Ivan; Preiner, Reinhold; Schreck, Tobias; Bustos, Benjamin; Digne, Julie and Crane, Keenan
In digital archaeology, a large research area is concerned with the computer-aided analysis of 3D captured ancient pottery objects. A key aspect thereby is the analysis of motifs and patterns that were painted on these objects' surfaces. In particular, the automatic identification and segmentation of repetitive patterns is an important task serving different applications such as documentation, analysis and retrieval. Such patterns typically contain distinctive geometric features and often appear in repetitive ornaments or friezes, thus exhibiting a significant amount of symmetry and structure. At the same time, they can occur at varying sizes, orientations and irregular placements, posing a particular challenge for the detection of similarities. A key prerequisite to develop and evaluate new detection approaches for such repetitive patterns is the availability of an expressive dataset of 3D models, defining ground truth sets of similar patterns occurring on their surfaces. Unfortunately, such a dataset has not been available so far for this particular problem. We present an annotated dataset of 82 different 3D models of painted ancient Peruvian vessels, exhibiting different levels of repetitiveness in their surface patterns. To serve the evaluation of detection techniques of similar patterns, our dataset was labeled by archaeologists who identified clearly definable pattern classes. Those given, we manually annotated their respective occurrences on the mesh surfaces. Along with the data, we introduce an evaluation benchmark that can rank different recognition techniques for repetitive patterns based on the mean average precision of correctly segmented 3D mesh faces. An evaluation of different incremental sampling-based detection approaches, as well as a domain specific technique, demonstrates the applicability of our benchmark. With this benchmark we especially want to address the geometry processing community, and expect it will induce novel approaches for pattern analysis based on geometric reasoning like 2D shape and symmetry analysis. This can enable novel research approaches in the Digital Humanities and related fields, based on digitized 3D Cultural Heritage artifacts. Alongside the source code for our evaluation scripts we provide our annotation tools for the public to extend the benchmark and further increase its variety.
Context-based Surface Pattern Completion of Ancient Pottery
(The Eurographics Association, 2022) Lengauer, Stefan; Preiner, Reinhold; Sipiran, Ivan; Karl, Stephan; Trinkl, Elisabeth; Bustos, Benjamin; Schreck, Tobias; Ponchio, Federico; Pintus, Ruggero
Among various ancient cultures it was common practice to adorn pottery artifacts with lavish surface decoration. While the applied painting styles, color schemes and displayed mythological content may vary greatly, the presence of simple patterns which appear in a repetitive manner can be observed across civilizations and periods. Such pattern sequences generally are arranged in a structured manner in ornament bands or columns that extend over the entire surface of the object. Due to the poor conservation state of many cultural heritage objects, parts of the surface are oftentimes badly damaged or missing altogether. Yet, if the majority of a pattern sequence is preserved, this information can be leveraged to approximate its missing parts. We present an approach that allows the fully automatic determination of the generation rule inherent to a repetitive surface pattern. Based on this generation rule and the preserved patterns from the same pattern class we propose a workflow for reconstruct missing or damaged parts of the surface painting. We evaluate our approach by applying it to a selection of pottery from ancient Peruvian and Greek cultures, showing that our automatic approach is able to handle a variety of problem cases.
Direct Elastic Unrollings of Painted Pottery Surfaces from Sparse Image Sets
(The Eurographics Association, 2021) Houska, Peter; Lengauer, Stefan; Karl, Stephan; Preiner, Reinhold; Hulusic, Vedad and Chalmers, Alan
An important task in archaeological research is the comparison of painted motifs on ancient vessels and the analysis of their painting style. Ideally, the pottery objects are available as scanned 3D models, from which the painted surface can be unrolled and potential distortions minimized, so that the vase painting and its individual motifs can be directly inspected. Unfortunately, the percentage of digitally captured vessels is small compared to the large body of cataloged photographs. In this paper, we present a method that creates distortion-minimized unrollings of painted pottery surfaces directly from a small set of photographs. We achieve this by exploiting prior knowledge about the data, namely that most objects exhibit rotational symmetry and that strict guidelines were followed when capturing photographs of the ancient vases. Based on the distinctly visible object silhouettes in the photographs we are able to extract proxy geometries of the objects which we encode as per-view geometric maps. By stitching the single-view data, we obtain a combined map capturing the geometry and texture of the entire painted surface. This enables us to minimize typical projective distortions by elastic relaxation. Our pipeline works entirely in 2D image space, circumventing time-consuming 3D scans and surface reconstructions of (often inaccessible) vessels. Using a combination of CPU-based image processing and GPU-based relaxation, results are produced in only a few minutes.
Motif-driven Retrieval of Greek Painted Pottery
(The Eurographics Association, 2019) Lengauer, Stefan; Komar, Alexander; Labrada, Arniel; Karl, Stephan; Trinkl, Elisabeth; Preiner, Reinhold; Bustos, Benjamin; Schreck, Tobias; Rizvic, Selma and Rodriguez Echavarria, Karina
The analysis of painted pottery is instrumental for understanding ancient Greek society and human behavior of past cultures in Archaeology. A key part of this analysis is the discovery of cross references to establish links and correspondences. However, due to the vast amount of documented images and 3D scans of pottery objects in today's domain repositories, manual search is very time consuming. Computer aided retrieval methods are of increasing importance. Mostly, current retrieval systems for this kind of cultural heritage data only allow to search for pottery of similar vessel's shape. However, in many cases important similarity cues are given by motifs painted on these vessels. We present an interactive retrieval system that makes use of this information to allow for a motif-driven search in cultural heritage repositories. We address the problem of unsupervised motif extraction for preprocessing and the shape-based similarity search for Greek painted pottery. Our experimental evaluation on relevant repository data demonstrates effectiveness of our approach on examples of different motifs of interests.
Recognizing User Behavior from Interactions for Adaptive Consumer Information Systems
(The Eurographics Association, 2023) Lengauer, Stefan; Bedek, Michael A.; Kupfer, Cordula; Shao, Lin; Albert, Dietrich; Schreck, Tobias; Pelechano, Nuria; Liarokapis, Fotis; Rohmer, Damien; Asadipour, Ali
Consumer Information Systems, which experience widespread application, benefit substantially from adapting the conveyed information to specific user needs, by addressing various impairments such as color blindness, deficient preknowledge, and/or graph illiteracy. Ideally, to allow for an unperturbed exploration process, the system automatically recognizes and responds to the need for adaptation. While it has been shown that users' interactions with a system can be leveraged to this end, there exists no generalized taxonomy covering all possible interactions/processes and how they relate to each other. This paper garners different interactions, defined in the literature, and classifies them regarding complexity and inter-dependencies in a 'processes landscape'. Using this landscape, we outline a concept how low-level interactions (e.g., 'Clicking', 'Typing') can be combined with context-sensitive ones (e.g., 'Hovering') to estimate high-level behavior such as 'Reading' or 'Exploring'. Knowledge of the latter allows a system to intervene and adapt in a reasonably manner.
Semi-automated Annotation of Repetitive Ornaments on 3D Painted Pottery Surfaces
(The Eurographics Association, 2020) Lengauer, Stefan; Komar, Alexander; Karl, Stephan; Trinkl, Elisabeth; Sipiran, Ivan; Schreck, Tobias; Preiner, Reinhold; Spagnuolo, Michela and Melero, Francisco Javier
The creation of drawings from the surface of painted pottery artifacts is an important practice in archaeological research and documentation. Traditional approaches include manual drawings using pen and paper, either directly on the physical surface, or from photographs, while more recent approaches are supported by photography or flattening of 3D digitized objects. Elaborate vase paintings, mostly showing figural scenes, often comprise ornamental decorations in secondary position or in the background, exhibiting repetitive patterns. We propose a tool supporting the creation of archaeological drawings with a semi-automatic extraction of ornamental surface sections, based on a combination of user-defined queries and self-similarity detection. Appropriate heuristics allow to detect the presence and positions of ornamental bands, a frequently occurring scheme, where ornamental primitives are evenly spaced along the tangential direction of a vessel's solid of revolution. Our interactive tool allows domain experts to efficiently select ornamental queries, and assess the quality of resulting similarity detections. First experiments with real world artifacts from ancient Greek and Peruvian cultures confirm the feasibility of the approach.
Sketch-Aided Retrieval of Incomplete 3D Cultural Heritage Objects
(The Eurographics Association, 2019) Lengauer, Stefan; Komar, Alexander; Labrada, Arniel; Karl, Stephan; Trinkl, Elisabeth; Preiner, Reinhold; Bustos, Benjamin; Schreck, Tobias; Biasotti, Silvia and Lavoué, Guillaume and Veltkamp, Remco
Due to advances in digitization technology, documentation efforts and digital library systems, increasingly large collections of visual Cultural Heritage (CH) object data becomes available, offering rich opportunities for domain analysis, e.g., for comparing, tracing and studying objects created over time. In principle, existing shape- and image-based similarity search methods can aid such domain analysis tasks. However, in practice, visual object data are given in different modalities, including 2D, 3D, sketches or conventional drawings like profile sections or unwrappings. In addition, collections may be distributed across different publications and repositories, posing a challenge for implementing encompassing search and analysis systems. We introduce a methodology and system for cross-modal visual search in CH object data. Specifically, we propose a new query modality based on 3D views enhanced by user sketches (3D+sketch). This allows for adding new context to the search, which is useful e.g., for searching based on incomplete query objects, or for testing hypotheses on existence of certain shapes in a collection. We present an appropriately designed workflow for constructing query views from incomplete 3D objects enhanced by a user sketch based on shape completion and texture inpainting. Visual cues additionally help users compare retrieved objects with the query. We apply our method on a set of relevant 3D and view-based CH object data, demonstrating the feasibility of our approach and its potential to support analysis of domain experts in Archaeology and the field of CH in general.
Towards Crowd-Sourced Collaborative Fragment Matching
(The Eurographics Association, 2023) Houska, Peter; Kloiber, Simon; Masur, Alessandra; Lengauer, Stefan; Karl, Stephan; Preiner, Reinhold; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
Many artifacts of our archaeological heritage are preserved only in fragments. The reassembly of these parts to their original form is therefore an essential task for archaeologists. Our project aims at incorporating the intellect of many participants from the broad public in the solution of this complex task. To this end, we develop a web-based 3D environment, in which users can interactively and collaboratively reassemble virtual fragments of real-world artifacts, supported by computer-aided methods. Our primary research focus lies on identifying how to best design and setup such a system in order to maximize the collaboration efficiency. By participating in this open reassembly process, users can gain valuable insight into the archaeological task, thus raising awareness for our common cultural heritage in a multitude of people.
Visual Exploration of Cultural Heritage Collections with Linked Spatiotemporal, Shape and Metadata Views
(The Eurographics Association, 2020) Lengauer, Stefan; Komar, Alexander; Karl, Stephan; Trinkl, Elisabeth; Preiner, Reinhold; Schreck, Tobias; Krüger, Jens and Niessner, Matthias and Stückler, Jörg
The analysis of Cultural Heritage (CH) artefacts is an important task in the Digital Humanities. Increasingly, rich CH artefact data comprising metadata of different modalities becomes available in digital libraries and research data repositories. How- ever, the large amounts and heterogeneity of artefacts in these repositories compromise their accessibility for common domain analysis tasks, as domain researchers lack a structural overview of the spatial, temporal, and categorical traits of the artefacts in these collections. Still, researchers need to compare artefacts along different modalities, put them into context, and deal with possible uncertainties, subjectivities, or missing data. To date, many works support domain research via interactive visuali- sation. The majority relies primarily on visualisation of text and metadata including spatiotemporal, image and shape data. However, fewer consider these types of data in a tightly coupled way. We present an approach for tightly integrated multimodal visual exploration of large CH data collections along space, time and shape traits. Based on requirements obtained in collab- oration with domain researchers, we introduce a set of interlinked views for exploration of said modalities. An appropriately defined approach automatically computes most significant correlations across different modalities, guiding the user towards de- tecting interesting artefact relationships. We apply our approach to pertinent archaeological data collections, and demonstrate that characteristic explorative tasks are effectively supported and domain-relevant artefact relations can be discovered.

Browsing by Author "Lengauer, Stefan"

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