MPG ETH CLS Student Projects


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Learning to predict wind flows for fixed-wing UAVs

This project will aim towards development of fast, accurate simulation approaches for predicting spatially-varying wind fields on-board a UAV.

machine learning fluid dynamics physics simulation unmanned aerial vehicles deep learning

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Learning Control

Machine learning for advanced control of intelligent systems

Control machine learning adaptive control robotics dynamic systems optimization intelligent systems

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Efficient automated texture recognition and mapping for 3D city models (assigned)

The purpose of dense 3D reconstruction is to obtain models that can be visualized on computers. Research on the topic focuses especially on improving the quality of the geometry in order to obtain models that are close to reality or making it faster in real-time.

Material/Texture Recognition Texture Mapping Segmentation 3D Models Machine Learning Computer Vision

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Simplifizierung von Dreiecksmodellen unter Berücksichtigung Geometrischer und Radiometrischer Eigenschaften

The Photogrammetry and Remote Sensing lab implemented an algorithm for the image-based reconstruction of surface meshes. Thereby an initial approximation of the surface is successively refined in a coarse-to-fine scheme.

Mesh Simplification 3D Reconstruction Airborne Images Photogrammetry Computer Vision

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