less or no labeled training data exists for fisheye pictures. Especially the semantic segmentation requires a pixel by pixel labeling. This cannot be done manually without an extreme amount of resources. Instead, we suggest to use synthetic data for the training. If these are as realistic as possible, these images can be used for training and create a model working on real world data. In order to create these images urban traffic scenes by Unity3D are used.