Abstract: A method for measuring the influence of a transparent pane. In the method, a displacement field induced by the pane is determined. In a first step, a first image of a textured surface without the transparent pane is acquired; in a second step, a second image of the textured surface with the transparent pane is acquired; and in a third step, the displacement field is determined by analyzing the two images using an optical flow method.

Abstract: A learning-based method for estimating self-movement and items of distance information in a camera system having at least two cameras, according to which temporally successive individual images produced by each camera during the movement of the camera system are supplied as input images to a self-monitored deep neural network of a deep learning system. According to the method, the self-monitored neural network is trained using these individual images. Moreover, in the course of the inference the deep learning system produces, from the input images, output data that describe the movement of the camera system.

Abstract: A method for lossy compression of measured data obtained through physical observation of a detection area. The method includes: the measured data and/or data prepared therefrom are divided with respect to at least one criterion into a plurality of classes and/or regions; the classes and/or regions are assigned priorities with respect to the intended evaluation of the measured data or to the data prepared therefrom; temporal changes of the measured data and/or of the data prepared therefrom divided into each class or region are compressed in a lossy manner, the degree of compression being a function of the priority assigned to the class or region. A method for monitoring a vehicle driving in traffic, and/or for controlling a vehicle driving at least in a semi-automated manner in traffic using the method for lossy compression, a compression module, camera, radar module or LIDAR module, and computer program, are also described.