Peters - Research Projects


  • Semantic Segmentation of Point Clouds using Semi Supervised Transfer Learning
    Semantic segmentation in 3d describes a point wise classification of point clouds. We think this task is challenging because on one side it is hard for humans to annotate the necessary data, because objects may appear ambiguous and labelling in 3d can be time consuming. On the other hand it appears that there is still no preferred way of how the data should be processed in order to use it with deep neural networks.
    Leaders: Brenner
    Team: Peters, Brenner
    Year: 2017
    Sponsors: DFG-Graduiertenkolleg i.c.sens

Research Projects

  • Processing of large-scale data sets in the context of autonomous driving
    The research training group i.c.sens has produced large quantities of data to support scientific research in the context of autonomous driving. To this end, multiple cars have been equipped with complex sensor setups for self-localization and mapping, including multiple GNSS systems, stereo cameras and multiple LiDAR systems. In order to enable secondary usage of these data sets and to publish the data set at a later point in time, the data needs to be prepared using established sensor-specific data processing methods or manual data annotation processes (e.g. labeling of images or point clouds towards a reliable ground-truth). The range of possible activities (programming, using a GIS for analyses, manual editing/annotation of data using provided tools and many more) in this research project is wide and can support multiple students at the same time. However, there is a lot of flexibility in determining the specific tasks to carry out (in a meeting before starting the research project).
    Leaders: Kuntzsch, Peters
    Year: 2018