Topics

Here you find different topics for student research that can be custom tailored to research projects (INF-PM-FPA,INF-PM-FPG,CMS-PRO), Großer Beleg or student theses in a discussion with the supervisor. As a prerequisite students should have attended one or better several of our master level courses.

Theses, Große Belege and Research Projects

  • Brain Twisters (4D and more)
    • Efficient Out-of-Core Slicing of Multi-Dimensional Data, Stefan Gumhold
      Here we consider a scalar dataset organized in an nD-Array or n-Tensor, which is a vector for n=1, a matrix for n=2 and a volume for n=3. Besides space dimensions (x,y,z) further dimensions like time (t) and frequency (f) can be sampled providing multi-dimensional datasets with n>4. In practical applications these are very large and won't fit in main memory. This thesis should investigate an out-of-core strategy to support 1D, 2D and optionally 3D slicing of the data along any combination of axes. There core of this thesis is to come up with a data organization on disk that supports real-time streaming of 1D, 2D, 3D slices to support interactive exploration of the multi-dimensional dataset.
  • Immersive Technology

    • Immersive drone control with preview of planned trajectory Zihan Zhang
      Drones have become an easy to use tool for scene acquisition. In this topic a programmable drone shall be combined with an AR headset in an outdoor environment. The AR glasses allow to visualize mission plans and the AR controllers can be used to define and edit mission plans. The goal is an immersive drone mission planning and execution tool.

    • AR treatment of anxiety disorders, Stefan Gumhold
      Current AR technology has reached a state where useful applications are possible. One of the most important applications of AR is the treatment of axiety disorders, which include claustrophobia, fear of height or speaking in public or spiders, etc. In this student work for one disorder a AR training tool should be developed and evaluated.

  • Rendering

    • [RESERVED] Random Generation of Plausible Human Poses Julien Fischer
      Machine learning models require a lot of data during training. For use-cases regarding digital human twins, the AMASS dataset is often times used. While AMASS contains many human motion sequences, it's corpus of motion data is still limited. To generate even more possible training data, this topic should investigate how random human poses can be generated in a way such that the resulting poses are plausible (e.g. no self interpenetrations). Interesting sub-problems could also be how to restrict the randomly generated poses to certain types of movements (e.g. walking, rowing with the arms)

  • Virtual Humans
    • Improving the Expressivity in Garment Modeling Kristijan Bartol
      Physical garments include various garment types and geometries, varying with respect to season, purpose, and appearance. Accurate 3D garment modeling is particularly relevant in virtual try-on applications, ensuring the reliability and realism of the virtual fit to various human body shapes. The project is based on the existing garment model developed at the CGV, with a focus on realistic garment modeling with sewing patterns. The goal of the project is to expand the current expressivity of the garment model, currently limited to shirts, pants, and dresses. The more expressive garment model can include hoodies, jackets, skirts, multi-layer garments, collars, pockets, etc. However, the project is not constrained to particular garment types and leaves room for creative proposals of more expressive garment types and their implementation.
  • Scientific Visualization 
    • Interactive visualization of spiraling optical coherent tomography imagery, Stefan Gumhold

    • Particle tracking velocimetry in foams using radiography, Sascha Heitkam (pdf)

Topics already taken

  • Brain Twisters
  • Immersive Technology
  • Virtual Humans

    • Physics-Based Simulations (PBS) for Clothed Virtual Humans, Kristijan Bartol

      Avatar-Configurator: Assigning clothes and assets to a virtual human avatar slides

    • Estimating Textures from an Image of a Clothed Person, Kristijan Bartol
  • Rendering

    • Remote Interaction for Visualization and Labeling

    • 4D hash map for trajectory relation visualization
      Trajectory datasets describe the choreographic motion of multiple entities like cars, drones, pedestrians, field game players, objects in flows and many more. To analyze the choreographic motion patterns relationships between closeby movers should be explorable in real-time. To find all close movers in a trajectory dataset a 4D hash grid shall be developed and its performance shall be tested on sample trajectory datasets of different sizes.

  • Scientific Visualization

    • Guidance for Oblique Slicing, Stefan Gumhold

    • Visualization of 3D Trajectories of Agents that see, Benjamin Russig

    • Multi-channel Transfer Function Design for analyzing sliced microscopy data (within PoL), Stefan Gumhold

    • Immersive visualization of Morpheus' cellular automata simulation
      (see Morpheus project page),  Stefan Gumhold
    • Texture space grids with ticks and labels, Stefan Gumhold
    • Interactive Visualization of Extreme Subset Sets, Stefan Gumhold
    • Visualization of multi-variate 2D scalar fields

    • Visualization of 2D Trajectory with Orientation, Stefan Gumhold

    • Visualization of 3D Trajectories with Orientation, Benjamin Russig

    • Data Reduction for Trajectories Represented by Hermite Splines, Benjamin Russig

  • User Guided Image Restauration with Invertible Neural Networks, Stefan Gumhold
    Invertible Neural Networks (INN) can map data distributions invertably to a uniform Gaussian distribution in a latent space of the same dimension as the input space. In this work INNs shall be used for image restauration by generating for a given corrupted input image a trajectory in latent space based on gradient ascent of the Gaussian probability distribution. Mapping the trajectory back to image space yields an image morph from the destorted image into the image manifold of the distribution learned by the INN. A user interface shall be provided to allow for interactive exploration of this image morph that can be used for user guided image restauration.          

  • Machine Learning Foundations, Dmitrij Schlesinger

    • Generative Feed Forward Networks pdf

  • Shadow Visualization in Urban Environments Using Open Data, Lennart Woidtke
    Shadows significantly influence urban planning and the comfort of city dwellers, especially on hot days. This topic leverages detailed open data from Dresden, including information on buildings and trees, to create a realistic 3D visualization of the city, dynamically showcasing available shade at different times of the day and year. Students will use geographic information system (GIS) data to model buildings and individual trees, considering attributes such as tree height, type, crown, and trunk diameters to accurately simulate the shadows they cast. A unique feature of this visualization will be the ability to adjust the shadow coverage based on the size of pedestrians, providing insights into sun exposure for individuals of different heights. The topic will require working with GIS data and implementing a realistic rendering pipeline, with the choice of framework left to the student.

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Stefan Gumhold
Last modified: Jun 04, 2025