Speaker: Schindler, Marwin (TU Wien)
Abstract:
Comparative visualization describes methods that are developed to find similarities or differences within data. The resulting techniques are embedded in a broad range of scientific disciplines and applied to a great variety of data. Scientific fields like medicine, geodesy, architecture, or industrial design, all work with different data modalities, but have in common that they require means to compare 3D spatial data. In this thesis, we want to investigate new possibilities for comparing differences between large spatial data ensembles in the form of multiple point clouds, which are not required to share shape characteristics or acquisition parameters. To do so, we will semi-automatically establish an order within the given ensemble that eases the comparison for users, by giving an explicit sequence in which ensemble members can be compared. An incentive behind this is to let users quickly move through the whole dataset by morphing from one ensemble member to the next one in a smooth animation, which serves as an overview, but also engages the recipients.