Abstract: The present disclosure relates to a filling body for reducing a volume of a pressure measurement chamber, which is to be filled with a pressure transmitting fluid, surrounding a pressure sensor. The filling body includes a recess for receiving the pressure sensor and has a free-standing base projecting into the recess on which the pressure sensor can be mounted. A filling body base supporting the filling body is provided on a side of the filling body facing away from the recess. The filling body can be mounted in an application location in such a way that the filling body base supports the otherwise free-standing filling body. The filling body base has a base surface that is smaller than a base surface of a filling body region that is adjacent to the filling body base and surrounding the recess.

Abstract: A home energy system for storing and providing energy.

Abstract: A method of processing image data in a connectionist network comprises a plurality of units, wherein the method implements a multi-channel unit forming a respective one of the plurality of units, and wherein the method comprises: receiving, at the data input, a plurality of input picture elements representing an image acquired by means of a multi-channel image sensor, wherein the plurality of input picture elements comprise a first and at least a second portion of input picture elements, wherein the first portion of input picture elements represents a first channel of the image sensor and the second portion of input picture elements represents a second channel of the image sensor; processing of the first and at least second portion of input picture elements separately from each other; and outputting, at the data output, the processed first and second portions of input picture elements.

Abstract: A system for detecting hand gestures in a 3D space comprises a 3D imaging unit. The processing unit generates a foreground map of the at least one 3D image by segmenting foreground from background and a 3D sub-image of the at least one 3D image that includes the image of a hand by scaling a 2D intensity image, a depth map and a foreground map of the at least one 3D image such that the 3D sub-image has a predetermined size and by rotating the 2D intensity image, the depth map and the foreground map of the at least one 3D image such that a principal axis of the hand is aligned to a predetermined axis in the 3D sub-image. Classifying a 3D image comprises distinguishing the hand in the 2D intensity image of the 3D sub-image from other body parts and other objects and/or verifying whether the hand has a configuration from a predetermined configuration catalogue. Further, the processing unit uses a convolutional neural network for the classification of the at least one 3D image.

Abstract: Disclosed is an easily manufacturable pressure measuring system comprising a support, especially a support of metal, especially stainless steel, a pedestal connected with the support, and a pressure sensor mounted on a free end of the pedestal, in the case of which the pressure sensor is protected against thermomechanical stresses. The pressure measuring system is distinguished by features including that the pedestal includes a base arranged on the support, the pedestal includes a projection extending from the base toward the pressure sensor and comprising the free end of the pedestal, the base has a footprint, which is larger than a footprint of the projection, and the projection has a footprint, which is smaller than a footprint of the pressure sensor mounted thereon.

Abstract: A method for lane detection for a camera-based driver assistance system includes the following steps: image regions in images that are recorded by a camera are identified as detected lane markings if the image regions meet a specified detection criterion. At least two detected lane markings are subjected to a tracking process as lane markings to be tracked. By means of a recursive state estimator, separate progressions are estimated for at least two of the lane markings to be tracked. Furthermore, for each of a plurality of the detected lane markings, a particular offset value is determined, which indicates a transverse offset of the detected lane marking in relation to a reference axis. By means of an additional estimation method, the determined offset values are each associated with one of the separate progressions of the lane markings to be tracked.

Abstract: In a method of generating a training image for teaching of a camera-based object recognition system suitable for use on an automated vehicle which shows an object to be recognized in a natural object environment, the training image is generated as a synthetic image by a combination of a base image taken by a camera and of a template image in that a structural feature is obtained from the base image and is replaced with a structural feature obtained from the template image by means of a shift-map algorithm.

Abstract: A method of determining the distance of an object from an automated vehicle based on images taken by a monocular image acquiring device. The object is recognized with an object-class by means of an image processing system. Respective position data are determined from the images using a pinhole camera model based on the object-class. Position data indicating in world coordinates the position of a reference point of the object with respect to the plane of the road is used with a scaling factor of the pinhole camera model estimated by means of a Bayes estimator using the position data as observations and under the assumption that the reference point of the object is located on the plane of the road with a predefined probability. The distance of the object from the automated vehicle is calculated from the estimated scaling factor using the pinhole camera model.

Abstract: A method for lane detection for a camera-based driver assistance system includes the following steps: image regions in images that are recorded by a camera are identified as detected lane markings if the image regions meet a specified detection criterion. At least two detected lane markings are subjected to a tracking process as lane markings to be tracked. By means of a recursive state estimator, separate progressions are estimated for at least two of the lane markings to be tracked. Furthermore, for each of a plurality of the detected lane markings, a particular offset value is determined, which indicates a transverse offset of the detected lane marking in relation to a reference axis. By means of an additional estimation method, the determined offset values are each associated with one of the separate progressions of the lane markings to be tracked.