Abstract: A control unit and a method for activating an occupant protection unit for a vehicle are provided, the occupant protection unit being activated as a function of a first signal of a first sensor system. The activation is validated as a function of an additional sensor signal, which validation is performed by gating at least one acceleration signal and at least one structure-borne noise signal as the sensor signals.

Abstract: Embodiments of the present invention provide a system, method, and program product to determine whether a product has been successfully purchased by identifying in a video record when a movement of a product adjacent to a scanner occurs, and whether the scanner did not record a purchase transaction at that time; measuring a difference in time between the time of the movement of the product and a time of another movement of a product, and determining by a trained support vector machine a likelihood that the product was successfully purchased. Alternately, the difference in time can be measured between the time of the movement of the product and a time of a transaction record, or between the time of the movement of the product and a boundary time. The support vector machine can use a radial basis function kernel and can generate a decision value and a confidence score.

Abstract: Embodiments of the present invention provide a system, method, and program product to determine whether a product has been successfully purchased by identifying in a video record when a movement of a product adjacent to a scanner occurs, and whether the scanner did not record a purchase transaction at that time; measuring a difference in time between the time of the movement of the product and a time of another movement of a product, and determining by a trained support vector machine a likelihood that the product was successfully purchased. Alternately, the difference in time can be measured between the time of the movement of the product and a time of a transaction record, or between the time of the movement of the product and a boundary time. The support vector machine can use a radial basis function kernel and can generate a decision value and a confidence score.

Abstract: A driver monitoring system for a motor vehicle has: at least one camera device including a cylindrical lens holder having at least one lens; at least one lighting element configured as an infrared radiator, and at least one plug-on module having a plate-shaped bearer on which the at least one lighting element is situated, the at least one plug-on module being configured to be plugged onto the lens holder.

Abstract: Video image data is acquired from synchronized cameras having overlapping views of objects moving past the cameras through a scene image in a linear array and with a determined speed. Processing units generate one or more object detections associated with confidence scores within frames of the camera video stream data. The confidence scores are modified as a function of constraint contexts including a cross-frame constraint that is defined by other confidence scores of other object detection decisions from the video data that are acquired by the same camera at different times; a cross-view constraint defined by other confidence scores of other object detections in the video data from another camera with an overlapping field-of-view; and a cross-object constraint defined by a sequential context of a linear array of the objects, spatial attributes of the objects and the determined speed of the movement of the objects relative to the cameras.

Abstract: A method for summarizing image content from video images received from a moving camera includes detecting foreground objects in the images, determining moving objects of interest from the foreground objects, tracking the moving objects, rating movements of the tracked objects, and generating a list of highly rated segments within the video images based on the ratings.

Abstract: A method for summarizing image content from video images received from a moving camera includes detecting foreground objects in the images, determining moving objects of interest from the foreground objects, tracking the moving objects, rating movements of the tracked objects, and generating a list of highly rated segments within the video images based on the ratings.

Abstract: A global position of an observed object is determined by obtaining a first global position of an observed object with at least one positioning device. A determination is made as to whether a set of stored visual characteristic information of at least one landmark matches a visual characteristic information set obtained from at least one captured image comprising a scene associated with the observed object. In response to the set of stored visual characteristic information matching the obtained visual characteristic information set, a second global position of the observed object is determined based on a set of stored location information associated with the at least one landmark and the first global position.

Abstract: A global position of an observed object is determined by obtaining a first global position of an observed object with at least one positioning device. A determination is made as to whether a set of stored visual characteristic information of at least one landmark matches a visual characteristic information set obtained from at least one captured image comprising a scene associated with the observed object. In response to the set of stored visual characteristic information matching the obtained visual characteristic information set, a second global position of the observed object is determined based on a set of stored location information associated with the at least one landmark and the first global position.

Abstract: A multichannel sensor unit includes: a multichannel sensor detecting at least one physical variable and outputting sensor data representing the detected physical variable; a main memory storing the sensor data of at least two sensor channels; and at least one additional memory. Instantaneous sensor data are stored in response to a trigger signal in the main memory. The sensor unit outputs first sensor data of a first sensor channel, which are stored in the main memory, in response to a first read command, and stores the additional sensor data in the at least one additional memory in response to the first read command. The sensor unit outputs the sensor data stored in the at least one additional memory in response to a second read command, such that the sensor unit outputs the sensor data from the main memory and the additional memory asynchronously.

Abstract: A method for summarizing image content from video images received from a moving camera includes detecting foreground objects in the images, determining moving objects of interest from the foreground objects, tracking the moving objects, rating movements of the tracked objects, and generating a list of highly rated segments within the video images based on the ratings.

Abstract: An apparatus, computer program product, and method for reducing persistent shadows within an image. The apparatus includes a camera configured to generate frames of the image. The apparatus also includes a computer processor. The computer processor calculates the average normalized brightness for each pixel in the image and adjusts the brightness of each pixel with the average normalized brightness.

Abstract: An apparatus, computer program product, and method for reducing persistent shadows within an image. The apparatus includes a camera configured to generate frames of the image. The apparatus also includes a computer processor. The computer processor calculates the average normalized brightness for each pixel in the image and adjusts the brightness of each pixel with the average normalized brightness.

Abstract: An apparatus, computer program product, and method for reducing persistent shadows within an image. The apparatus includes a camera configured to generate frames of the image. The apparatus also includes a computer processor. The computer processor calculates the average normalized brightness for each pixel in the image and adjusts the brightness of each pixel with the average normalized brightness.

Abstract: An apparatus, computer program product, and method for reducing persistent shadows within an image. The apparatus includes a camera configured to generate frames of the image. The apparatus also includes a computer processor. The computer processor calculates the average normalized brightness for each pixel in the image and adjusts the brightness of each pixel with the average normalized brightness.

Abstract: A method for summarizing image content from video images received from a moving camera includes detecting foreground objects in the images, determining moving objects of interest from the foreground objects, tracking the moving objects, rating movements of the tracked objects, and generating a list of highly rated segments within the video images based on the ratings.

Abstract: The disclosure relates to a method for evaluating structure-borne sound during a collision of a vehicle. The method includes filtering a structure-borne sound signal which represents a structure-borne sound propagating in the vehicle, having a plurality of filter rules. Each of the filter rules is configured to generate a filtered structure-borne sound signal from the structure-borne sound signal. The method further includes combining the filtered structure-borne sound signals into an evaluation signal.

Abstract: Visual content in images captured from a scene by a camera in each of a plurality of different pose settings are analyzed to determine predicted occurrences of a transaction associated with the visual content in each pose, which are compared with actual transaction occurrence data to generate performance values for each pose as a function difference between the predicted and actual transactions. Optimized poses are chosen having the best performance value, wherein a camera controller may place the camera in the optimum pose for use in monitoring the scene and generating the primitives of interest associated with the transactions.

Abstract: Events are classified through string pattern recognition. Text labels are assigned to image primitives in a time-ordered set of training images and to related time-ordered transactions in an associated training transaction log in a combined time-ordered training string of text labels as a function of image types. Transactions are labeled in a training transaction log with a transaction label, a training primitive image of a start of a transaction with a start image text label, a training primitive of an entry of a transaction into the log with an entry image text label, and a training primitive of a conclusion of a transaction with an ending image text label. Positive subset string patterns are discovered representing true events from the combined time-ordered training string of text labels, and negative subset string patterns defined by removing single transaction primitive labels from the positive subset string patterns.

Abstract: A global position of an observed object is determined by obtaining a first global position of an observed object with at least one positioning device. A determination is made as to whether a set of stored visual characteristic information of at least one landmark matches a visual characteristic information set obtained from at least one captured image comprising a scene associated with the observed object. In response to the set of stored visual characteristic information matching the obtained visual characteristic information set, a second global position of the observed object is determined based on a set of stored location information associated with the at least one landmark and the first global position.