Ever since, load-carrying structures were required to be highly functional, cost efficient and environmentally compatible. Likewise, this applies to civil and mechanical engineering as well as to aerospace.
New composite materials, steady increase of computer performance and miniaturisation of sensors and electronics decisively influence the development trends for future load-carrying structures. Therefore, these structures will be multifunctional lightweight and durable.
The Institute of Structural Analysis at Leibniz Universität Hannover aims at these strategic objectives. Its research is focused on the areas of vibrations and composites.
Research at the Institute of Structural Analysis
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Paper published in PFG: Conditional Adversarial Networks for Multimodal Photo-Realistic Point Cloud Rendering
Torben Peters and Claus Brenner developed a method to create photorealistic visualizations from point clouds.
We investigate whether conditional generative adversarial networks (C-GANs) are suitable for point cloud rendering. For this purpose, we created a dataset containing approximately 150,000 renderings of point cloud–image pairs. The dataset was recorded using our mobile mapping system, with capture dates that spread across 1 year. Our model learns how to predict realistically looking images from just point cloud data. We show that we can use this approach to colourize point clouds without the usage of any camera images. Additionally, we show that by parameterizing the recording date, we are even able to predict realistically looking views for different seasons, from identical input point clouds.