Project description DEENESFRITPL New techniques for geometry processing of high-dimensional spaces Geometry processing borrows concepts from applied mathematics, computer science and engineering to design efficient algorithms for acquiring, analysing and manipulating complex 3D models. The field can be used to improve machine learning inference problems. However, fundamentally new algorithms are needed to compute geometric data in higher-dimensional spaces. The EU-funded EMERGE project aims to develop new geometric processing tools for use in data science. Researchers will introduce fundamentally new concepts for surface representations and computational methods for surface interrogation in dimensions higher than three. Project results will have a profound impact on the analysis of the increasing amount of unstructured quantitative data stemming from sensors. Show the project objective Hide the project objective Objective Geometry Processing is concerned with algorithms and data structures for representing and processing three-dimensional shapes. Techniques in geometry processing have been developed over the last three decades and are now driving real-world applications in various industries. Geometry processing algorithms may be interpreted as components of digital signal processing or machine learning, solving inference problems: given an incomplete description of the geometry, commonly based on point samples, the concept or process underlying the observations - the surface - is recovered (unsupervised feature learning) and then may be smoothed (filtering), segmented (clustering), or interactively modified (semi-supervised learning). To facilitate these operations the surface representation is adjusted (transcoding, resampling). However, using the algorithms and data structures in geometry processing for data living in higher dimensional spaces requires fundamentally new methods in geometric computing. Emerge presents a research program aiming at making geometry processing methods available as a set of tools in data science. Emerge will introduce fundamentally new concepts for surface representations and computational methods for surface interrogation in dimension beyond three -- providing useful tools in various science and engineering disciplines. The thesis of Emerge is that the resulting extensions and generalizations of geometry processing techniques will be fruitfully complementing and adding to the state of the art in processing large amounts of data. Any progress in this direction will have profound impact, as the proliferation of sensors and data processing has led to most of the current societal challenges (climate change, global biological risks, population growth, global policy making, energy) coming with enormous amounts of unstructured quantitative data to be analyzed. Fields of science natural sciencescomputer and information sciencescomputational sciencenatural sciencesmathematicspure mathematicsgeometrynatural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changesnatural sciencescomputer and information sciencesartificial intelligencemachine learningnatural sciencescomputer and information sciencesdata sciencedata processing Programme(s) HORIZON.1.1 - European Research Council (ERC) Main Programme Topic(s) ERC-2021-ADG - ERC ADVANCED GRANTS Call for proposal ERC-2021-ADG See other projects for this call Funding Scheme HORIZON-AG - HORIZON Action Grant Budget-Based Coordinator TECHNISCHE UNIVERSITAT BERLIN Net EU contribution € 2 496 559,00 Address Strasse des 17 juni 135 10623 Berlin Germany See on map Region Berlin Berlin Berlin Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
