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3D Reconstruction and Modeling across Different Levels of Abstraction

Objective

"Digital 3D models are gaining more and more importance in diverse application fields ranging from computer graphics, multimedia and simulation sciences to engineering, architecture, and medicine. Powerful technologies to digitize the 3D shape of real objects and scenes are becoming available even to consumers. However, the raw geometric data emerging from, e.g., 3D scanning or multi-view stereo often lacks a consistent structure and meta-information which are necessary for the effective deployment of such models in sophisticated down-stream applications like animation, simulation, or CAD/CAM that go beyond mere visualization. Our goal is to develop new fundamental algorithms which transform raw geometric input data into augmented 3D models that are equipped with structural meta information such as feature aligned meshes, patch segmentations, local and global geometric constraints, statistical shape variation data, or even procedural descriptions. Our methodological approach is inspired by the human perceptual system that integrates bottom-up (data-driven) and top-down (model-driven) mechanisms in its hierarchical processing. Similarly we combine algorithms operating on different levels of abstraction into reconstruction and modeling networks. Instead of developing an individual solution for each specific application scenario, we create an eco-system of algorithms for automatic processing and interactive design of highly complex 3D models. A key concept is the information flow across all levels of abstraction in a bottom-up as well as top-down fashion. We not only aim at optimizing geometric representations but in fact at bridging the gap between reconstruction and recognition of geometric objects. The results from this project will make it possible to bring 3D models of real world objects into many highly relevant applications in science, industry, and entertainment, greatly reducing the excessive manual effort that is still necessary today."
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Principal Investigator

Leif Kobbelt (Prof.)

Host institution

RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN

Address

Templergraben 55
52062 Aachen

Germany

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 2 482 000

Principal Investigator

Leif Kobbelt (Prof.)

Administrative Contact

Ernst Schmachtenberg (Prof.)

Beneficiaries (1)

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RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN

Germany

EU Contribution

€ 2 482 000

Project information

Grant agreement ID: 340884

Status

Closed project

  • Start date

    1 March 2014

  • End date

    28 February 2019

Funded under:

FP7-IDEAS-ERC

  • Overall budget:

    € 2 482 000

  • EU contribution

    € 2 482 000

Hosted by:

RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN

Germany