The field of Comparative Visualization struggles with finding effective ways to compare multiple visual elements to one another. For example, it addresses the problem of trying to understand how multiple ensembles of contours or 3D meshes differ from each other. Although many approaches have been proposed , most of do not tackle appropriately scalability, i.e., when the number of elements to compare increases, the method does not perform well. This becomes even worse, when we have 4D data, e.g. 3D meshes changing through time.
The task of this project is to design and implement scalable, expressive and intuitive strategies for the comparative visualization of 3D and 4D data. These strategies will be based on state-of-the-art methods from the domain of Comparative Visualization and Visual Analytics. More details about the subtasks and the workflow of the topic will be provided upon request.
The project should be implemented as a standalone application, desktop or web-based (tools to be discussed).
 Comparison techniques utilized in spatial 3D and 4D data visualizations: A survey and future directions - Kim et al., 2017
 YMCA: Your Mesh Comparison Algorithm - Schmidt et al., 2014
 Time-hierarchical clustering and visualization of weather forecast ensembles - Ferstl et al., 2017
 Pelvis Runner - Grossmann et al., 2019