4D-CH-WORLD · Four Dimensional Cultural Heritage World
7РП — „Хора“ (Действия „Мария Кюри“)
- Период
- 2013-01-01 → 2016-12-31
- Финансиране от ЕС
- 1 360 093 €
- Участници
- 8
- Схема
- MC-IAPP
Линиите свързват координатора с партньорите.
Накратко на български
Алгоритми за компютърно зрение и машинно обучение създават 4D цифрови карти на културни обекти, като например паметника Порта Нигра. Това позволява възстановяване на разрушени паметници чрез анализ на снимки и данни от социални мрежи.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Four Dimensional Cultural Heritage World
4D-CH-Word is a Marie Curie project funded by European Union with the main purpose of designing, analyzing, researching and developing computer vision and machine learning algorithms for a cost-effective creation of 4D digital maps in cultural heritage. 4D digital modelling implies the creation of precise time-varying 3D reconstructions of cultural heritage objects to capture temporal geometric variations/distortions, i.e., a spatio-temporal assessment. The key research challenge for 4D modelling, was the data collection over heterogeneous unstructured web resources. Such “in the wild” data include outliers and significant noise, since they have not been created for 3D modelling and reconstruction purposes. In addition, GPS and geo-information is limited or non-existent. However, such data allow for a massive reconstruction of the content even for monuments that have been destroyed due to natural phenomena or humans’ interventions. The project exploits digital information from both unstructured data, available over distributed multimedia repositories and social networks, and from in-situ data acquisition procedures. The 4D digital modelling methods were testing in Calw, a town in the middle of Baden-Württemberg, located 40 km southwest of Stuttgart. Other demonstration scenarios refer to the digital reconstruction of the monument of Porta Nigra in Germany and Padrão dos Descobrimentos in Portugal. The first step involved the content-based retrieval of visual information from distributed multimedia databases, like Picasa, Flickr and Twitter. Machine learning methods, exploiting unsupervised clustering algorithms, were used to isolate data outliers and group together similar data with respect to their visual properties. Additionally, textual analysis and processing take place to assign semantic metadata (tags) to the visual collected data. As far as the in-situ data collection process in concerned, terrestrial laser scanning, close-range photographs and aerial imagery have been used. All these information are appropriately fused, using computer vision algorithms, machine learning methods and photogrammetry tools for a cost-effective, automated and precise time varying 3D modelling. 4D-CH-World supported various capturing procedures, including generation of dense 3D point clouds and terrestrial and aerial overlapping images. In the context of data analysis, novel computer vision tools have been adopted for fusing the heterogeneous collected data to improve the precision and accuracy of modelling towards an automated framework. Finally, synthetic data and computer graphics methods are exploited to fill out missing information from the data acquisition process. To implement the time dimension of the modelling, data from different time instances have been collected. It is clear that for content referring to past periods, only RGB image data are available. These data are collected through developed search engine, retrieving images over distributed databases and the social media. More specifically, for the Calw case our data go back to 1850s and 1860s, when the first glass-plate photographs could be collected. In order to understand and classify spatio-temporal regions in historic urban cities, deep learning strategies are employed. The term deep learning refer to a variety of techniques that can understand complicated patterns by automatically extracting the appropriate features for the task. In the context of 4D-CH-Word, we have focused on convolutional neural networks (CNNs) for two different scenarios; a) timber house identification and b) urban development monitoring. The deep learning approaches supported the 4D reconstruction; i.e., understanding the time period of the reconstructed areas by either, separating new from old buildings, or newly developed areas. In the end, deep learning and advanced filtering approaches allowed the creation of image clusters according to the time period. The 4D-CH-World outcomes are presented via 4D visualization toolkits. The visualization methods have been developed in a Web-based interface. A user is able to freely navigate within the reconstructed environment and interact with it. Texturized detailed models depict accurate the current place, providing further information when requested by the user. Furthermore, for specific areas, user can experience the evolution through the years; see the current monument, how it was the previous decades and view the raw images that supported the 3D reconstruction. Finally, by selecting a year as a reference (e.g. 2000), we can see (if available) the difference in a specific area just by activating the time filter. That way, the 4D-CH-word team, successfully combined 3D models of a scene associated to different time instances, developing a system for 4D reconstruction and visualization of the results. The final research achievement of 4D-CH-Word deal with recommendation system able to filter content according to both user preferences and visual attributes. The recommendation system empowers the user to interact with the platform and selects CH objects of interest displayed to him/her through suitable profiles. Users’ profiles are created by measuring the feedback of the users to the system through the activation of recursive machine learning algorithms that on-line update the system response to fit user’s preferences. The produced software was designed for tablets and phones. It is also possible to run the platform in a standard desktop PC. However, touch screen is strongly suggested. The user is able to navigate freely to the 3D world either as pedestrian (road view) either from above. At specific areas, indicated on the map, we are able to see the actual image that led to the creation of the 3D object. The tools developed are currently exploited for the digitalization of intangible cultural heritage such as dances through a collaboration with the TERPSICHORE and iTreasures EU funded projects. The innovative tools are also exploited under the framework of the international project being currently in progress regarding the restoration of the Holy Aedicule of the Holy Sepulcher Church in Jerusalem.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
This project4D-CH-World aims to analyze, design, research, develop and validate an innovative system integrating the latest advances in computer vision and learning, as well as, 3D modeling and virtual reality for the rapid and cost-effective 4D maps reconstruction in the wild for personal use, and support the aim of our European Commons and the digital libraries EUROPEANA and UNESCO Memory of the World (MoW) to build a sense of a shared European cultural history and identity.The main goal of the 4D-CH-World is to enable historians, architects, archaeologists, urban planners, or any other affiliated scientists to reconstruct from available data on repositories, study, understand, preserve or document urban environments, as well as, organizing collections of thousands of images (spatially and temporally) in generating novel views of historical scenes by interacting with the time-varying model itself. The evolving steps depiction helps understanding the cultural trends, performing behavioral analysis, exploiting the impact of the available raw resources in building development, further analyzing the urban economy factors, and simulating a future urban growth in order to understand the future demands, and satisfy in time the people’s concrete needs. Education system will have the opportunity to exploit this innovative system to motivate students and help them better understand many things in an amusing way. Finally, pupils, university students, tourists, communes, future mechanics and economists, will observe urban environment changes through time, not just read it, and therefore understand it, so as, future plans of action, regarding urban renewal or sustainable development would be less likely to fail.
Оригинален текст от CORDIS (на английски).
Участници
- TECHNICAL UNIVERSITY OF CRETE · CHANIAКоординаторГърция
- 7REASONS MEDIEN GMBH · AbsdorfАвстрия
- DIGINEXT · AIX EN PROVENCEФранция
- ETHNICON METSOVION POLYTECHNION · ATHINAГърция
- EXUS SOFTWARE LTD · LondonОбединеното кралство
- FRAUNHOFER GESELLSCHAFT ZUR FORDERUNG DER ANGEWANDTEN FORSCHUNG EV · MunchenГермания
- TECHNOLOGIKO PANEPISTIMIO KYPROU · LemesosКипър
- UNIVERSITY OF STUTTGART · StuttgartГермания
Връзки
Данни: CORDIS, © Европейски съюз
