Robert Boschgmbh

Gregor Blott

Jan Rexilius

Masato Takami

Damian Koesters

Stefan Nordbruch

Christian Neumann

Uwe Brosch

Matthias Roland

Christian Stresing

Fabian Brickwedde

Sascha Florian Lange

Robert Borchers

A method for determining video segments to be transferred of a video, which is recorded in a vehicle using a camera. The method including, for one or for each of multiple video segments of the videos recorded in the vehicle, analyzing the one or one of each of the multiple video segments with respect to its respective content, generating data, which include pieces of information relating to the respective content of a respective video segment, conveying the data to an extra-vehicular processing system, receiving pieces of information about one or about multiple video segments to be transferred from the extra-vehicular processing system and transferring the one or the multiple video segments to be transferred to the extra-vehicular processing system. A method carried out in the processing system, a camera system, and a processing system are also described.

Method for determining video segments to be transferred

A method for determining a noteworthy sub-sequence of a monitoring image sequence of a monitoring area. The method includes: providing an audio signal from the monitoring area, at least partially including a time period of the monitoring image sequence; providing the monitoring image sequence of the environment to be monitored, which has been generated by an imaging system; determining at least one segment of the audio signal from the provided audio signal, which has unusual noises; determining at least one segment of the monitoring image sequence having unusual movements within the environment to be monitored; determining a correlation between the at least one segment of the audio signal having unusual noises and the at least one segment of the monitoring image sequence with unusual movements in order to determine a noteworthy sub-sequence of the monitoring image sequence.

Method for determining a noteworthy sub-sequence of a monitoring image sequence

A surveillance system having an interface to a camera network for video surveillance of a surveillance area. The camera network includes a plurality of cameras each for capturing a surveillance subarea. The cameras are designed to provide surveillance images of the surveillance subareas. The surveillance system also includes a surveillance device for re-identifying people in the surveillance images. The surveillance device includes a person detection module for detecting people and an object detection modulefor detecting objects. The surveillance deviceincludes an assignment moduledesigned to assign at least one item of object information to a person, and an action detection moduledesigned to detect an action of the personon one of the objects

Surveillance system, method, computer program, storage medium and surveillance device

A method for generating a monitoring image. The method includes: providing an image sequence of the surroundings to be monitored with the aid of an imaging system; determining at least one monitoring area and at least one periphery area of at least one image of the image sequence with the aid of a learning-based semantic segmentation method; compressing the monitoring area of the at least one image of the image sequence with a first compression quality; and compressing the periphery area of the at least one image of the image sequence with a second compression quality to generate the compressed monitoring image, the second compression quality being lower than the first compression quality.

Method for generating a monitoring image

The invention relates to a monitoring device () for recognizing persons in a monitoring region (), the monitoring region () being video-monitored by means of at least one camera () and the camera () being designed to provide monitoring images () to the monitoring device () as video data, the monitoring device comprising: —a feature determination apparatus (), the feature determination apparatus () being designed to determine a feature vector () for each object in at least one of the monitoring images (); —a person recognition apparatus (), the person recognition apparatus () being designed to detect in the monitoring images () a person to be recognized (), on the basis of the determined feature vector and/or the determined feature vectors () of the feature determination apparatus () and/or a combined feature vector (); —an association apparatus (), the association apparatus () being designed to determine a feature vector () for each person to be recognized () and each associated environment object of the person to be recognized (), the association apparatus () being designed to determine the combined feature vector () on the basis of the feature vector () of the person to be recognized () and the feature vector or the feature vectors () of the associated environment objects.

Monitoring device, monitoring system, method, computer program and machine-readable storage medium

A monitoring systemis proposed, having a camera networkfor the video-based monitoring of a monitoring region, wherein the camera networkcomprises a plurality of camerasfor recording a partial monitoring regionof the monitoring regionin each case, wherein the plurality of camerasare configured to provide monitoring imagesof the partial monitoring regions, having at least one sensor devicefor detecting at least one person-related object information item, having a monitoring devicefor recognizing personsin the monitoring images, wherein the monitoring devicecomprises a person detection module, the person detection modulebeing configured to detect personsin the monitoring images, wherein the monitoring devicecomprises an assignment module, the assignment modulebeing configured to assign an item of person-related object information from a partial monitoring regionto a personin the same partial monitoring regionand to provide it as personal data, wherein the monitoring devicecomprises a comparison module, the comparison modulebeing configured to compare personal data from a plurality of different partial monitoring regions, wherein if a match is found in the personal data from at least two partial monitoring regions, a personis recognized in the monitoring images

Video based monitoring system using multiple cameras, method, computer program and storage medium

An anonymization apparatusis proposed for the generation of anonymized images, wherein surveillance imagesare provided through video surveillance of a surveillance regionby means of at least one camera, with a recognition module, wherein the surveillance imagesare provided to the recognition module, wherein the recognition moduleis configured to recognize personscontained in the surveillance images, with a processing module, wherein the processing moduleis configured to process the surveillance imagesinto the anonymized images, wherein at least one personor person segment included in the surveillance imagesis anonymized in the anonymized images, wherein the processing moduleis configured to replace the recognized personor person segment by an animated person modelfor the purpose of anonymization.

Anonymization apparatus, surveillance device, method, computer program and storage medium

Person recognition device for person re-identification in a monitoring region, having a camera apparatus and an evaluation module, wherein the camera apparatus comprises a first camera unit and a second camera unit, wherein the first camera unit is configured to record a first monitoring image of a portion of the monitoring region, wherein the second camera unit is configured to record a second monitoring image of the portion of the monitoring region, wherein the camera apparatus is configured to feed the first monitoring image and the second monitoring image to the evaluation module, wherein the evaluation module is configured to re-identify a person in the monitoring region based on the first monitoring image and the second monitoring image, wherein the second camera unit has a cut-off filter for wavelength cutting of incident light in a stop band.

Person recognition device and method

A method for training a person recognition model using images from a camera, wherein the method has at least a reading-in step in which a detection signalrepresenting a detected person within a monitoring area of at least the camerain a camera network is read in. The method also has at least a collecting step in which a plurality of image signalsfrom the cameraare collected using the detection signalwhich has been read in, wherein the collected image signalsrepresent a recorded image section from each image from the camera. Finally, the method has at least an adapting step in which the person recognition model is adapted using the collected image signalsin order to recognize the detected person in an image from the cameraor from an at least second camera in the camera network.

Method for training a person recognition model using images from a camera, and method for recognizing persons from a trained person recognition model by means of a second camera in a camera network

Monitoring apparatusfor person recognition in a monitoring region, having at least one camerafor recording an image sequence of a portionof the monitoring region, wherein the image sequence comprises a plurality of monitoring images, having a person recognition module, wherein the person recognition modulehas at least one recognition feature of a person that is to be located and is configured to search for the person to be recognized based on the monitoring images and the recognition feature, wherein the camerahas a fisheye lens

Monitoring apparatus for person recognition and method

A method for setting a camera, in particular of a monitoring device, comprising a recording of an image of a region to be monitored, an analysis of the recorded image to associate at least one image region of the image with an object, identification of the object on the basis of the acquired image region and ascertainment of a size of the object by access to stored size information of the identified object and a scaling of the image region associated with the object in the recorded image to scale the remaining acquired image and/or to determine a distance of the camera to the acquired object.

Method for setting a camera

A method for object identification is described, the method initially including a step of reading in, in which input data signals, as well as a determined camera control parameter for adjusting a recording feature of a camera are read in. The input data signals in this case represent the images of the object to be identified that are recorded by at least one camera. Finally, the method includes a step of identification, in which the object is identified in a neural network using the determined camera control parameter.

Method and device for object identification

A method for calibrating a camera. The method includes a step of reading in and a step of ascertaining, an imaging trajectory and a reference trajectory of a moving calibration object detected by using the camera being read in in the step of reading in, the imaging trajectory representing a trajectory imaged in image coordinates of the camera and the reference trajectory representing the trajectory in world coordinates, and at least one calibration parameter for the camera being ascertained in the step of ascertaining by using the imaging trajectory and the reference trajectory.

Method for calibrating a camera and calibration system

A method for controlling a motor vehicle includes steps of scanning an environment of the motor vehicle, controlling the motor vehicle as a function of the scanned information, ascertaining a driving situation of the motor vehicle, and of activating, deactivating or parameterizing a protective function of the motor vehicle as a function of the ascertained driving situation.

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Salzgitter, Germany

Gregor Blott