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Geometry Processing as Inference

Project description

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.

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.

Host institution

TECHNISCHE UNIVERSITAT BERLIN
Net EU contribution
€ 2 496 559,00
Address
STRASSE DES 17 JUNI 135
10623 Berlin
Germany

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Region
Berlin Berlin Berlin
Activity type
Higher or Secondary Education Establishments
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Total cost
€ 2 496 559,00

Beneficiaries (1)