Virtual architectural reconstructions have been developed for nearly four decades now, with the London Charter providing a framework for their scholarly use, particularly emphasising the need for transparent and evaluable documentation. Despite this, documentation remains uncommon due to the absence of binding standards, limited incentives, and the considerable effort required. Crucially, experience shows that documentation cannot realistically be produced retrospectively and must be created alongside with the reconstruction process. To address this gap, IDOVIR, a platform supported by the German Research Foundation (DFG), aims to streamline documentation workflows and improve communication among researchers by providing an efficient, web-based framework for recording and sharing information. More than ten years of experience with such approaches have both refined existing methods and highlighted the need for broader standardisation. The community is increasingly seeking to define general principles, criteria, and best practices for high-quality documentation beyond project-specific solutions. This paper contributes to that effort by outlining key requirements, proposing structural guidelines, and compiling relevant source types for reconstructions, with the goal of fostering consensus and improving the transparency, understanding, and evaluation of virtual reconstruction projects. With our proposal, we want to intensify the necessary communication process in the community to establish coordinated standardisation, which is lacking at the moment.

Virtual reconstructions in the fields of architecture, archaeology, and cultural heritage are based on a variety of sources and arguments that should be documented in a comprehensible manner (paradata). A comprehensive, standardized classification of sources tailored explicitly for virtual reconstructions would greatly facilitate the creation of comparable and objective documentation. To address both, the DFG-funded project IDOVIR is developing a freely accessible online tool for the structured documentation of reconstruction processes. Despite some proposed vocabularies, a comprehensive source classification still does not exist. To this end, a hierarchical classification scheme of sources with seven primary outline levels has been developed, which is based on existing vocabularies and experiences from real projects. Each source can be further described using objective criteria (e.g., source type, context of origin, scale). According to Linked Open Data principles, the terms are linked to controlled vocabularies such as Getty AAT, GND, or Wikidata to enable interoperability and integration into research infrastructures (e.g., NFDI, EOSC). The classification system and the tool are currently brought to discussion within the community and continuously developed. Another key feature of IDOVIR is comparative visualization, which allows sources and 3D reconstructions to be viewed side by side, overlaid, and analysed. This supports the critical evaluation of reconstruction proposals during the development process.

Source-based virtual reconstructions have become essential tools for communication and research in urban and architectural studies. While these reconstructions are often showcased through exhibition visualizations, the underlying knowledge is not always apparent or even documented. This raises concerns about their sustainability. Without transparent, publicly accessible documentation of the decision-making processes (known as paradata) that come with and support these digital reconstructions, there is a risk of losing both the knowledge embedded in them and their potential scientific value. To enhance transparency and allow for proper assessment and recognition of these reconstructions, thorough documentation and evaluation of the reconstruction processes are crucial. Although there are various approaches to documenting virtual reconstructions tailored to specific use cases, and while some focus on aspects like visualizing reliability, the overall process of documentation remains cumbersome and costly, making it an exception rather than the norm. Previous tools that claim to properly document virtual reconstructions either cover only part of the metadata and linked sources, are too complicated to use, or are no longer available. Currently, there is no universally accepted, straightforward, and easy-to-use workflow for this purpose. The IDOVIR project addresses this gap by offering a user-friendly, web-based platform designed specifically for documenting digital architectural reconstructions. We strive for achieving such a standardized workflow. To date, the platform has already been adopted by a large number of users, and many projects are publicly accessible.

Abstract In the context of source-based virtual reconstructions and its underlying decision-making processes (paradata), there has been a long-time demand for documenting why a reconstruction was executed in a certain way, and presenting it in a comprehensible and public manner. Lacking documentation leads to a loss of knowledge and that the scientific nature of a reconstruction won’t be guaranteed anymore. Based on earlier prototypes, TU Darmstadt and HTW Dresden developed IDOVIR (Infrastructure for Documentation of Virtual Reconstructions) which enables the documentation of this kind of paradata and metadata, and, at the same time, supports communication during the reconstruction phase. The tool can be used free of charge and independently by registering via ORCID. The core of IDOVIR is the division of an entity into different spatial areas and time periods to which multiple variants can be assigned. Each variant contains the triple of 1) the representation of the reconstruction (2D or 3D), 2) the sources used, and 3) a textual argumentation that explains how the reconstruction has been inferred from the sources. For long-term storage and availability, IDOVIR is hosted by the University and State Library Darmstadt.

The ongoing digitization of historical photographs in archives allows investigating the quality, quantity, and distribution of these images. However, the exact interior and exterior camera orientations of these photographs are usually lost during the digitization process. The proposed method uses content-based image retrieval (CBIR) to filter exterior images of single buildings in combination with metadata information. The retrieved photographs are automatically processed in an adapted structure-from-motion (SfM) pipeline to determine the camera parameters. In an interactive georeferencing process, the calculated camera positions are transferred into a global coordinate system. As all image and camera data are efficiently stored in the proposed 4D database, they can be conveniently accessed afterward to georeference newly digitized images by using photogrammetric triangulation and spatial resection. The results show that the CBIR and the subsequent SfM are robust methods for various kinds of buildings and different quantity of data. The absolute accuracy of the camera positions after georeferencing lies in the range of a few meters likely introduced by the inaccurate LOD2 models used for transformation. The proposed photogrammetric method, the database structure, and the 4D visualization interface enable adding historical urban photographs and 3D models from other locations.

Virtual reconstructions have become widely established as communication and research tools in the context of architectural and urban studies.To make these reconstruction solutions more transparent and to allow for their assessment and recognition, it is of vital importance to document and evaluate the reconstruction processes.However, currently, such documentation, which would facilitate the scholarly analysis of the results, is only compiled in isolated cases.The DFGfunded project IDOVIR (Infrastructure for Documentation of Virtual Reconstructions) provides the community with a freely accessible, free of charge, and userfriendly platform (https://idovir.com)for documenting sources, reconstructions and decisions quickly and economically.From variants and different evaluation schemes for reconstructions and sources, the versatile tool allows the user to indicate the plausibility and informational value of the sources and the reconstructions based on them.

We present methods to visualize characteristics in collections of historical photographs, especially focusing on the presentation of spatial position and orientation of photographs in relation to the buildings they depict. The developed methods were evaluated and compared in a user study focusing on their appropriateness to gain insight into specific research questions of art historians: 1) which buildings have been depicted most often in a collection of images, 2) which positions have been preferred by photographers to take pictures of a given building, 3) what is the main perspective of photographers regarding a specific building. To analyze spatial datasets of photographs, we have adapted related methods used in the visualization of fluid dynamics. As these existing visualization methods are not suitable in all photographic situations—especially when a multitude of photographs are pointing into diverging directions—we have developed additional cluster-based approaches that aim to overcome these issues. Our user study shows that the introduced cluster-based visualizations can elicit a better understanding of large photographic datasets concerning real-world research questions in certain situations, while performing comparably well in situations where existing methods are already adequate.

Digitized historical photographs are invaluable sources and key items for scholars in Cultural Heritage (CH) research. Properties of photographic items, such as position and orientation of the camera, can be automatically estimated using Structure from Motion (SfM) algorithms to enable spatial queries on image repositories. Interactive spatial and temporal browsing of photographs of architecture and corresponding 3D models allows historians to gain knowledge about the development of a city, as well as about the changing interest of photographers in depicting particular buildings over time. In this chapter, we present a classification of phenomena modeling the statistical distribution of historical photographic depictions of architecture. This classification serves the design of specialized visualization methods that show statistical aggregation of photographs in spatial contexts, thus supporting research workflows of art and architectural historians.

Introduction and objective Although being standard for scoliosis curve size estimation, COBB angle measurement is well known to be inaccurate, due to a high interobserver variance in end vertebra selection and end plate contour delineation. We propose a stepwise improvement by using a spline constructed from vertebra centroids to resemble spinal curve characteristics more closely. To enhance precision even further, a neural net was trained to detect the centroids automatically. Materials & Methods Vertebra centroids in AP spinal X-ray images of varying quality from 551 scoliosis patients were manually labeled by 4 investigators. With these inputs, splines were generated and the computed curve sizes were compared to the manually measured COBB angles and to the curve estimation obtained from the neural net. Results Splines achieved a higher interobserver correlation of 0.92–0.95 compared to manual COBB measurements (0.83–0.92) and showed 1.5–2 times less variance, depending on the anatomic region. This translates into an average of 1° of interobserver measurement deviation for spline-based curve estimation compared to 3°–8° for COBB measurements. The neural net was even more precise and achieved mean deviations below 0.5°. Conclusion In conclusion, our data suggest an advantage of spline-based automated measuring systems, so further investigations are warranted to abandon manual COBB measurements.

Muscular activity during human motion is usually quantified by measuring the electrical potential during muscle activation using electromyography (EMG). However, apart from producing electrical activity, muscular contraction of many skeletal muscles also induces subtle deformation of the skin surface. In this paper, we present a method to estimate muscular activation from such 3D skin deformation. To this end, we introduce a capture system that reconstructs the 3D motion of the skin from multi-view video data and simultaneously measures true muscle activity with EMG sensors. Our data reveals strong correlations between the skin deformation and muscular activity during one-leg stances. We propose a pose normalization procedure and a novel model based on Supervised Principal Component Regression that automatically segments individual muscles and estimates their activation from 3D surface deformation. Our evaluation shows that the model generalizes to varying body shapes and that the estimated activation closely fits the measured EMG data.

Objective assessment in long-term rehabilitation under real-life recording conditions is a challenging task. We propose a data-driven method to evaluate changes in motor function under uncontrolled, long-term conditions with the low-cost Microsoft Kinect sensor. Instead of using human ratings as ground truth data, we propose kinematic features of hand motion, healthy reference trajectories derived by principal component regression, and methods taken from machine learning to analyze the progression of motor function. We demonstrate the capability of this approach on datasets with repetitive unrestrained bi-manual drumming movements in three-dimensional space of stroke survivors, patients suffering of Parkinson's disease, and a healthy control group. We present processing steps to eliminate the influence of varying recording setups under reallife conditions and offer visualization methods to support clinicians in the evaluation of treatment effects.

Archives and museums store vast collections of historical images of urban areas and make them publicly available through online platforms. Many of these images, often containing historic buildings and landscapes, can be oriented spatially using automatic methods such as structure from motion (SfM). Providing spatially and temporally oriented images of urban architecture, in combination with advanced searching and 2D/3D exploration techniques, offers new potentials in supporting historians in their research. We are developing a 3D web environment usable to historians to spatially search online media repositories containing historic photographic images. We combine 3D models of historic buildings with spatially oriented images, replacing text-based searching through meta-data with spatial and temporal browsing with respect to given focus points in historic city models.

Statistical body shape modelling can be used to realistically generate complex muscle deformation effects on the skin. However, purely data-driven models still ignore the biomechanical nature of surface deformations. Reliable anatomically and biomechanically consistent predictions are barely possible. Our research aims at combining the previously separate paradigms - data-driven and simulation-driven 3D surface modeling - to a hybrid body shape model. Our first goal consists of synthesizing the skin surface from simulated biomechanical data. As a first step in this direction we show preliminary results of our model of an elbow flexion motion with separate biceps and triceps muscle bulging that exhibits believable muscular deformation effects on the skin surface while enabling singular control over specific muscle regions. Our model is separately controllable in shape and pose and extensible to a wider range of human body shapes, joint motion and muscle regions.

In der Archaologie werden immer haufiger digitale Rekonstruktionen/Visualisierungen eingesetzt. Die bei solchen Rekonstruktionsprojekten anfallenden Daten sind fur externe Personen schwer in einen nachvollziehbaren Zusammenhang zu bringen. Fragestellungen, ob und auf welchen Fakten und Quellen die Rekonstruktion beruht, bleiben oft unbeantwortet. Das entwickelte Werkzeug unterstutzt die Entstehung und Dokumentation digitaler Rekonstruktionen und ermoglicht eine intuitive Suche in den verknupften Daten.

Digital reconstructions are becoming more and more common in archaeology and architecture. They visualize lost, but also present structures, can broaden the comprehension of a reconstructed object and point out historical and constructional relationships of the objects in consideration. Furthermore the process of reconstruction leads to an aggregation of knowledge and has become a substantial part of scientific work. However, such projects usually lack of a proper, traceable, and valuable documentation practice which is rigorously applied. In the final reconstruction state the reference of a source for a certain object may only been known to experts in the project. Understanding from an external point of view often becomes a cumbersome process. Until now, most research for documentation practice is concentrated to theoretical approaches; valuable practical tools are still missing. We introduce a documentation tool for 3d reconstruction supposed to accompany a project and to support frequent tasks in digital reconstruction processes. All used sources can be linked to the reconstructed objects. Simultaneously, the whole development process is logged automatically. The data is stored compliant to the CIDOC CRM in a graph database. With suitable navigation functionality the user can explore/compare the 3d-model together with the sources and information data. Furthermore there is a special mode for briefings and a version control to record all development steps. This tool not only may help enormously during the reconstruction process but also can be applied for final presentation of the results to experts or e.g. museum visitors.

This paper introduces compressed eigenfunctions of the Laplace-Beltrami operator on 3D manifold surfaces. They constitute a novel functional basis, called the compressed manifold basis, where each function has local support. We derive an algorithm, based on the alternating direction method of multipliers ADMM, to compute this basis on a given triangulated mesh. We show that compressed manifold modes identify key shape features, yielding an intuitive understanding of the basis for a human observer, where a shape can be processed as a collection of parts. We evaluate compressed manifold modes for potential applications in shape matching and mesh abstraction. Our results show that this basis has distinct advantages over existing alternatives, indicating high potential for a wide range of use-cases in mesh processing.