Abstract: Embodiments include techniques to determine a set of credit risk assessment data samples, generate local credit risk assessment attributions for the set of credit risk assessment samples, and normalize each local credit risk assessment attribution of the local credit risk assessment attributions. Further, embodiments techniques to compare each pair of normalized local credit risk assessment attributions and assign a rank distance thereto proportional to a degree of ranking differences between the pair of normalized local credit risk assessment attributions. The techniques also include applying a K-medoids clustering algorithm to generate clusters of the local risk assessment attributions, generating global attributions, and determining insights for the neural network based on the global attributions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for object detection. In one aspect, a method comprises: obtaining: (i) an image, and (ii) a set of one or more query embeddings, wherein each query embedding represents a respective category of object; processing the image and the set of query embeddings using an object detection neural network to generate object detection data for the image, comprising: processing the image using an image encoding subnetwork of the object detection neural network to generate a set of object embeddings; processing each object embedding using a localization subnetwork to generate localization data defining a corresponding region of the image; and processing: (i) the set of object embeddings, and (ii) the set of query embeddings, using a classification subnetwork to generate, for each object embedding, a respective classification score distribution over the set of query embeddings.

Abstract: Embodiments of the disclosure include a method, a device, and a computer program product for video processing. This method includes: selecting frames having features of a first type from a first instance of a video as a first candidate set, the first instance having a first resolution; generating a set of training frames based at least on the first candidate set; acquiring a set of corresponding frames for the set of training frames in a second instance of the video, the second instance having a second resolution lower than the first resolution; and determining, using the set of training frames and the set of corresponding frames, a conversion parameter for conversion from the second resolution to a third resolution. This solution provides a smaller-scale and higher-quality training set for the training of a video conversion model, thus improving the quality of training while saving computational resources and increasing training speed.

Abstract: A synthetic world interface may be used to model digital environments, sensors, and motions for the evaluation, development, and improvement of computer vision and speech algorithms. A synthetic data cloud service with a library of sensor primitives, motion generators, and environments with procedural and game-like capabilities, facilitates engineering design for a manufactural solution that has computer vision and speech capabilities. In some embodiments, a sensor platform simulator operates with a motion orchestrator, an environment orchestrator, an experiment generator, and an experiment runner to test various candidate hardware configurations and computer vision and speech algorithms in a virtual environment, advantageously speeding development and reducing cost. Thus, examples disclosed herein may relate to virtual reality (VR) or mixed reality (MR) implementations.

Abstract: Techniques for implementing unsupervised anomaly detection by self-prediction are provided. In one set of embodiments, a computer system can receive an unlabeled training data set comprising a plurality of unlabeled data instances, where each unlabeled data instance includes values for a plurality of features. The computer system can further train, for each feature in the plurality of features, a supervised machine learning (ML) model using a labeled training data set derived from the unlabeled training data set, receive a query data instance, and generate a self-prediction vector using at least a portion of the trained supervised ML models and the query data instance, where the self-prediction vector indicates what the query data instance should look like if it were normal. The computer system can then generate an anomaly score for the query data instance based on the self-prediction vector and the query data instance.

Abstract: An apparatus for estimating contact distribution to quickly estimate contact spot distribution from a contact surface image using a deep learning model based on a convolution neural network (CNN) and a method thereof are disclosed. A method for estimating contact distribution to estimate contact spot distribution between a first contact spot and a second contact spot includes inputting a contact surface image of at least one of the first contact surface and the second contact surface to a deep learning model based on a CNN and estimating contact spot distribution between the first contact surface and the second contact surface from an output of the deep learning model.

Abstract: Aspects of the technology described herein relate to techniques for guiding an operator to use an ultrasound device. Thereby, operators with little or no experience operating ultrasound devices may capture medically relevant ultrasound images and/or interpret the contents of the obtained ultrasound images. For example, some of the techniques disclosed herein may be used to identify a particular anatomical view of a subject to image with an ultrasound device, guide an operator of the ultrasound device to capture an ultrasound image of the subject that contains the particular anatomical view, and/or analyze the captured ultrasound image to identify medical information about the subject.

Abstract: Techniques related to object detection using an adaptive convolutional neural network (CNN) are discussed. Such techniques include applying one of multiple configurations of the CNN to input image data in response to an available computational resources for processing the input image data.

Abstract: In some examples, a computer system may receive an image and associated location information corresponding to a location at which the image was captured. The system may provide the image as input to a machine-learning model previously trained to determine whether the received image includes a threshold amount of information to indicate that received location information indicates a location corresponding to the received image. Based at least in part on an output of the machine-learning model indicating that the received image meets the threshold, the system may store the associated location information as mapping information associated with the location.

Abstract: An approach is disclosed for visually identifying and/or pairing ride providers and passengers. The approach involves, for example, receiving location data indicating that a driver vehicle is within a proximity threshold of a passenger pickup location. The approach also involves initiating an activation of a camera of a passenger device to present live imagery on the passenger device. The approach further involves processing sensor data collected from one or more sensors of the passenger device to determine a rotation vector indicating a pointing direction of the passenger device. The approach also involves determining a new direction to point the passenger device to capture the driver vehicle in a field of view of the camera based on the rotation vector and the location data. The approach further involves providing output data for presenting a representation of the new direction in a user interface of the passenger device.

Abstract: This application discloses a method for determining an implantation location of recommendation information performed at a computer device. The method includes: acquiring a target video; acquiring, according to a scene change status of the target video, a target video frame being used for location detection; performing image recognition on the target video frame to obtain masking information of the target video frame including a first region of an object of a target type in the target video frame; and determining an implantation location of recommendation information in the target video frame based on the first region. Image recognition processing is performed on the target video frame to obtain the masking information of the target video frame, so as to determine the implantation location in the target video frame on the basis of the first region corresponding to the object of the target type in the target video frame.

Abstract: According to some embodiments, a method includes accessing a video generated by a first physical camera in a physical environment. The method further includes identifying an object of interest in the video frame that corresponds to a physical object in the physical environment. The method further includes displaying a virtual 3D environment that corresponds to the physical environment. The method further includes configuring a plurality of settings of a first virtual camera to match a plurality of settings of a first physical camera and configuring a plurality of settings of a second virtual camera to match a plurality of settings of a second physical camera. The method further includes projecting the identified object of interest into the virtual 3D environment using the configured first and second virtual cameras.

Abstract: One variation of a method for monitoring occupancy in a work area includes, at a sensor block: transitioning from an inactive state into an active state when an output of a motion sensor indicates motion in a work area; during a scan cycle in the active state, recording an image through an optical sensor at a time, detecting a set of humans in the image, detecting a second set of human effects in the image, predicting a second set of humans occupying but absent the work area based on the second set of human effects, and estimating a total occupancy in the work area at the time based on the set of humans and the second set of humans; and transmitting the total occupancy to a remote computer system for update of a scheduler for the work area.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting locations in an environment of a vehicle where objects are likely centered and determining properties of those objects. One of the methods includes receiving an input characterizing an environment external to a vehicle. For each of a plurality of locations in the environment, a respective first object score that represents a likelihood that a center of an object is located at the location is determined. Based on the first object scores, one or more locations from the plurality of locations are selected as locations in the environment at which respective objects are likely centered. Object properties of the objects that are likely centered at the selected locations are also determined.

Abstract: Methods and systems for controlling an autonomous machine. The autonomous machine has sensors generating input data, while the controller includes two or more neural networks that inference using the input data and generate output data. The neural networks can be trained using an identical set of training data set. The output data from each of the neural networks are monitored to ensure that the integrity of the operation is maintained by, for example, the output data from one neural network is compared with the output data from another neural network to verify the consistency. If the comparison yields that the integrity of the system is not maintained at an acceptable level, the controller can stop using the output in controlling the autonomous machine.

Abstract: A vehicle position and velocity estimation system based on camera and LIDAR data is disclosed. An embodiment includes: receiving input object data from a subsystem of a vehicle, the input object data including image data from an image generating device and distance data from a distance measuring device, the distance measuring device comprising one or more LIDAR sensors; determining a first position of a proximate object near the vehicle from the image data; determining a second position of the proximate object from the distance data; correlating the first position and the second position by matching the first position of the proximate object detected in the image data with the second position of the same proximate object detected in the distance data; determining a three-dimensional (3D) position of the proximate object using the correlated first and second positions; and using the 3D position of the proximate object to navigate the vehicle.

Abstract: The disclosure discloses a historical map utilization method based on a vision robot, including: S1, the vision robot is controlled to continuously collect image of a preset road sign of a preset working area, and road sign information of the preset road sign is obtained; S2, the obtained road sign information is transmitted to a first map positioning system and a second map positioning system; S3, the first map positioning system and the second map positioning system are controlled to respectively process corresponding road sign information, thereby obtaining first pose information and second pose information; S4, the first pose information and the second pose information under the same preset road sign are selected, and a transformation relationship formula of the first pose information and the second pose information is calculated; and S5, the historical map is controlled to perform a corresponding transformation operation, and subsequent motion control is performed.

Abstract: A method and apparatus used for extracting a feature point of an environmental target, which relate to the field of vehicles. The method comprises: acquiring the position of each corner point of an environmental target; and determining a feature point of the environmental target according to the position of each corner point of the environmental target. Thus, the problem wherein target identification is not precise may be solved, which is particularly suitable for the identification of a large target.

Abstract: A vehicle position estimation device is configured to acquire a distance from a road edge to a subject vehicle using at least one of an imaging device or a distance measuring sensor, acquire position information of lane boundary lines detected by analyzing the images captured by the imaging device; acquire map information including a lane quantity of a traveling road of the subject vehicle from a map storage, calculate, as a roadside area width, a lateral direction distance between an outermost detection line, which is an outermost boundary line among the detected boundary lines, and the road edge, and specify a traveling lane of the subject vehicle based on (i) the distance from the road edge to the subject vehicle, (ii) the roadside area width, and (iii) the lane quantity included in the acquired map information.

Abstract: Methods and an apparatuses for recognizing a text, recognition devices and storage media are provided, which belong to the field of text detections. A method includes: extracting, by the recognition device, a feature map of a to-be-recognized image, then determining segmentation information of a text region of the to-be-recognized image based on a preset segmentation network and the feature map, and then determining boundary key points in the text region based on the segmentation information, and then converting a text in the text region into a text with a target arrangement sequence based on the boundary key points and then inputting the text obtained by conversion into a preset recognition model for recognition processing.

Abstract: Methods, systems, and wearable extended reality devices for generating a floorplan of an indoor scene are provided. A room classification of a room and a wall classification of a wall for the room may be determined from an input image of the indoor scene. A floorplan may be determined based at least in part upon the room classification and the wall classification without constraining a total number of rooms in the indoor scene or a size of the room.

Abstract: A camera (10) for detecting objects (48) moving relative to the camera (10) in a direction of movement (50), comprising an image sensor (18) for recording image data of the objects (48) in a camera field of view (14, 56), an optoelectronic distance sensor (24) using a time-of-flight method having a plurality of measurement zones (30a) for measuring a plurality of distance values to the objects (48) in a distance measurement field of view (58), and a control and evaluation unit (38) configured to find, by measuring distance values over a configuration time and evaluating the distance values and/or their change, a region where objects (48) move, and to automatically set a region of interest (60) for the distance sensor (24) within the distance measurement field of view (58) by determining an object region as the region where objects (48) move.

Abstract: Described herein is a mechanism for visual recognition of items or visual search using Optical Character Recognition (OCR) of text in images. Recognized OCR blocks in an image comprise position information and recognized text. The embodiments utilize a location-aware feature vector created using the position and recognized information in each recognized block. The location-aware features of the feature vector utilize position information associated with the block to calculate a weight for the block. The recognized text is used to construct a tri-character gram frequency, inverse document frequency (TGF-IDP) metric using tri-character grams extracted from the recognized text. Features in location-aware feature vector for the block are computed by multiplying the weight and the corresponding TGF-IDF metric. The location-aware feature vector for the image is the sum of the location-aware feature vectors for the individual blocks.

Abstract: This disclosure is directed to methods and systems that enable automatic recognition of the meaning, sentiment, and intent of an Internet meme. An Internet meme refers to a digitized image, video, or sound that is a unit of cultural information, carries symbolic meaning representing a particular phenomenon or theme, and is generally known and understood by members of a particular culture. The disclosed methods include automatic identification of a meme template and automatic detection of the sentiment and relationships between entities in the meme. The methods provide the determination of a meme's meaning as intended by its purveyors, as well as recognition of the original sentiment and attitudes conveyed by the use of entities within the meme.

Abstract: In some aspects, the disclosure is directed to methods and systems for automatic context-based annotation by leveraging a priori knowledge from annotations in template documents. A large library of template documents may be generated and pre-processed in many implementations to identify annotations or other inclusions commonly present on documents related to or conforming to the template. Newly scanned documents may be compared to these templates, and when a similar template is identified, annotation locations and types from the template may be applied to the newly scanned document to recognize and classify annotations and inclusions. To increase efficiency and provide scalability, comparisons of scanned documents and template documents may be distributed amongst a plurality of computing devices for processing in parallel, with similarity results aggregated.

Abstract: A system and method for domain aware document classification and information extraction from consumer documents are disclosed. A particular embodiment is configured to: establish, by use of a data processor and a data network, a data connection with at least one applicant platform; receive an upload of documents from the applicant platform via the data network; classify each document as being of a particular document type; determine an information extraction strategy based on a document type classification of a particular document; and extract information from the particular document based on the information extraction strategy.

Abstract: Systems and methods for document analysis using model intersections are disclosed. Predictive models are built and trained to predict whether a given document is in class with respect to a given model. Each predictive model may be associated with a subcategory of an identified technology. Documents that are determined to be in class by multiple ones of the predictive models may be identified and grouped into subsets. These subsets of documents may be identified as relevant to the technology in question.

Abstract: Techniques are disclosed for detecting an uncovered portion of a body of a person in a frame of video content. In an example, a first machine learning model of a computing system may output a first score for the frame based on a map that identifies a region of the frame associated with an uncovered body part type. Depending on a value of the first score, a second machine learning model that includes a neural network architecture may further analyze the frame to output a second score. The first score and second score may be merged to produce a third score for the frame. A plurality of scores may be determined, respectively, for frames of the video content, and a maximum score may be selected. The video content may be selected for presentation on a display for further evaluation based on the maximum score.

Abstract: A detection device includes a sensor unit, a detector configured to receive an output from a sensor, a detection controller configured to drive and control the sensor unit and the detector, and a processor configured to perform processing in accordance with an output from the detector. The detection controller drives the sensor unit and the detector and determines a touch detection duration in which a coordinate of a finger contacting or nearby the sensor unit is detected, and a fingerprint detection duration in which a fingerprint image of the finger is detected.

Abstract: The present invention provides a display device, which includes a frame having an accommodating cavity and a display module disposed in the accommodating cavity. The display module includes a first light source, an optical unit, an imaging unit arranged on a side of the optical unit facing away from the first light source, and a lens array arranged on a side of the imaging unit facing away from the first light source. Corresponding to a preset pattern, light emitted by the first light source passes through the optical unit, the imaging unit and the lens array to form a default floating image in a floating display area outside the accommodating cavity. In addition, the present invention also provides a non-contact key and an input device including the above display module.

Abstract: A device for capturing a biometric print of a user, the user compartment including a frontal opening designed for the passage of part of a hand into said user compartment and a lateral opening allowing the passage of the thumb of the user's hand, the lateral opening extending as far as the frontal opening to form a continuous open space, the lateral opening being delimited in a direction of insertion of the user's hand into the user compartment by a user hand positioning stop.

Abstract: The present disclosure provides a fingerprint collection method. When a fingerprint sensor is integrated on any function key of a terminal, a failure of a fingerprint application function that is caused when a user unintentionally operates a function key can be avoided. The method includes: obtaining, by a terminal, a fingerprint collection instruction, where the fingerprint collection instruction is used to instruct to collect a fingerprint by using a fingerprint sensor integrated on a function key; collecting, by the terminal by using the fingerprint sensor based on the fingerprint collection instruction, fingerprint information recorded by a user on the function key; obtaining, by the terminal on the function key at any moment of collecting the fingerprint information, a first key event triggered by the user, where the first key event is any operation other than a fingerprint recording event; and discarding, by the terminal, the first key event.

Abstract: Embodiments of the present application provide a fingerprint identification method, a fingerprint identification apparatus and an electronic device. The fingerprint identification method is applied to a fingerprint identification apparatus disposed under a display screen of an electronic device, the fingerprint identification apparatus includes a pixel array and a colour filter layer, the colour filter layer includes at least one filter unit, and the at least one filter unit is disposed above at least one first type pixel of the pixel array, respectively, and the method includes: capturing a first light signal transmitting through the at least one filter unit and sensed by the first type pixel; determining a fingerprint identification environment according to an intensity of the first light signal; and determining, based on the fingerprint identification environment, a target capturing parameter of capturing a fingerprint light signal, the fingerprint light signal being used for fingerprint identification.

Abstract: An electronic device is provided. The electronic device includes a display panel including an image sensor arranged to receive incident light reflected by an external object, a first guide structure arranged between the display panel and the image sensor and configured to change the direction of the incident light which is introduced through a fingerprint recognition area of the display panel, a second guide structure arranged between the first guide structure and the image sensor and configured to change the direction of the incident light which is introduced therein after passing through the first guide structure, and a processor operatively connected to the display panel and the image sensor. According to an embodiment, the electronic device performs fingerprint recognition by acquiring image information through the image sensor on the basis of at least a part of the incident light introduced through the first guide structure and the second guide structure.

Abstract: An electronic device includes a foldable housing including a hinge, a first housing connected to the hinge and including a first surface facing a first direction and a second surface facing a second direction opposite to the first direction, and a second housing connected to the hinge, the second housing including a third surface facing a third direction and a fourth surface facing a fourth direction opposite to the third direction, wherein the first housing and the second housing are foldable relative to each with respect to the hinge, and the first surface faces the third surface in a folded state and the third direction is the same as the first direction in an unfolded state, and a first display forming the first surface and the third surface and extending from the first surface to the third surface.

Abstract: An image acquisition device includes a single sensor having organic photodetectors, an angular filter, and a color filter. The color filter has one or a plurality of first portions adapted to give way to at least one wavelength in the visible range, and one or a plurality of second portions filtering wavelengths outside of red and/or near infrared. The second portion has a surface area approximately equal to a surface area of one of the photodetectors or a surface area greater than or equal to the surface area of four of the photodetectors.

Abstract: A photographing apparatus includes: an imaging unit which is arranged at a position opposed to a plurality of fingers to be presented, and is configured to image the plurality of fingers; and a plurality of light sources which are arranged in plurality in an array direction of the plurality of fingers, and are configured to irradiate the plurality of fingers with light from an outside of an opposing region in which the imaging unit is opposed to the plurality of fingers toward an inside of the opposing region.

Abstract: An apparatus, system and method for providing a visual search using augmented reality glasses. The apparatus, system and method include a network communicatively associated with the glasses capable of providing remote connectivity to an application programming interface (API); a machine learning (ML) model communicative with the API and having an input capable of receiving live video data indicative of a view field of the glasses, wherein the ML model includes at least a data comparator and platform-specific coding corresponded to the glasses; a search engine within the ML model and having a secondary input interfaced to a comparative database, wherein the search engine compares the live view field video data to the secondary input using the comparator; and a match output capable of outputting a match obtained by the search engine over the network to the glasses.

Abstract: Systems and methods for adapting physical activities and exercises based on facial analysis by image processing are disclosed. A method includes: identifying, by a computer device, a user; receiving, by the computer device, video data of a face region of the user while the user is engaged in exercise or physical activity; analyzing, by the computer device, the video data to determine a detected state of the user, wherein the analyzing the video data includes performing facial analysis using the video data; and providing, by the computer device, feedback to the user based on the analyzing the video data.

Abstract: Methods for operating a motion recognition apparatus are disclosed. In some implementations, a method for recognizing a motion or gesture of an object may include operating an optical sensor device to capture light reflected from the object under illumination by light emitted toward the object, generating, by comparing the emitted light to the reflected light, a depth image including distance information indicating a distance between the optical sensor device and the object, generating, based on the light reflected from the object, an infrared image including infrared image information associated with the object, and determining the motion of the object based on at least one of the depth image and the infrared image.

Abstract: An action recognition method includes: obtaining original feature submaps of each of temporal frames on a plurality of convolutional channels by using a multi-channel convolutional layer; calculating, by using each of the temporal frames as a target temporal frame, motion information weights of the target temporal frame on the convolutional channels according to original feature submaps of the target temporal frame and original feature submaps of a next temporal frame, and obtaining motion information feature maps of the target temporal frame on the convolutional channels according to the motion information weights; performing temporal convolution on the motion information feature maps of the target temporal frame to obtain temporal motion feature maps of the target temporal frame; and recognizing an action type of a moving object in image data of the target temporal frame according to the temporal motion feature maps of the target temporal frame on the convolutional channels.

Abstract: Methods, apparatus and systems for wireless gait recognition and rhythmic motion monitoring are described. In one example, a described system comprises: a transmitter, a receiver, and a processor. The transmitter is configured for transmitting a first wireless signal towards an object in a venue through a wireless multipath channel of the venue. The receiver is configured for: receiving a second wireless signal through the wireless multipath channel between the transmitter and the receiver. The second wireless signal differs from the first wireless signal due to the wireless multipath channel which is impacted by a rhythmic motion of the object. The processor is configured for: obtaining a time series of channel information (CI) of the wireless multipath channel based on the second wireless signal, monitoring the rhythmic motion of the object based on the time series of CI (TSCI), and triggering a response action based on a result of the monitoring.

Abstract: An electronic device and a control method therefor are disclosed. The present invention comprises: a camera; a memory for storing user face authentication information and an authentication pattern; and a control unit for recognizing a face from an image acquired through the camera, performing a first authentication that determines whether the recognized face matches the face authentication information, tracking the movement of a gaze of the recognized face when the first authentication is completed, and performing a second authentication that determines whether the movement of the gaze matches the authentication pattern. According to the present invention, a dual authentication step using the face authentication information and the movement of the gaze of the user can be conveniently performed.

Abstract: A fare gate in a transportation system including a barrier, a sensor, and an actuator. The actuator moves the barrier from the open position into the closed position. The sensor is mounted on the barrier and in one position captures sensor data across an aisle formed by the fare gate. A transit user in front of the barrier in another position is identified by the sensor. The transit user passes through the fare gate using the aisle. The actuator moves the barrier from a closed position to an open position to clear passage through the aisle. Using the sensor, the aisle is scanned with a movement of the barrier. The sensor is calibrated based on a predetermined point with movement of the barrier to align the sensor and the predetermined point.

Abstract: In some examples, a system may include a first computing device communicatively coupled to a second computing device. Additionally, the first computing device is configured to obtain, from the second computing device, check-in data indicating an arrival of the user of the second computing device at a first location, and in response to obtaining the check-in data, determine current wait times. Moreover, the first computing device is configured to determine a first number of customers waiting for service, determine a first number of associates available to assist the first number of customers, and determine an expected wait time for the user operating the second computing device based at least on the current wait times. In some examples, the first number of customers waiting for service, and the first number of associates available. Further, the first computing device is configured to transmit the expected wait time to the second computing device.

Abstract: A vehicle diagnostic system and related method comprises an interface component connected to a vehicle's On-Board Diagnostics (OBD) port, interface elements comprising: a short range communication module; and a vehicle network protocol interface; short range communication module designed to automatically constitute a data link with a mobile communication device running a gateway module; vehicle network protocol interface configured to intercommunicate bi-directionally with short range communication module to obtain requests from gateway module and to send vehicle data to gateway module: said vehicle network protocol interface further configured to communicate bi-directionally with OBD port to send requests to the vehicle's networks and to derive vehicle data therefrom.

Abstract: Embodiments of this disclosure disclose provisioning a cloud service on a vehicle. The method may include, in response to receiving a registration request for cloud services for a vehicle and determining a geographical location of the vehicle based on the registration request. The method may further include identifying cloud services available to the geographical location and extracting capability information of the vehicle from real time series data of the vehicle. The method may further include determining cloud services applicable to the vehicle from the cloud services available to the geographical location based on the extracted capability information of the vehicle and in response to receiving a service subscription request from the vehicle, provisioning on the vehicle a cloud service applicable to the vehicle corresponding to the service subscription request.

Abstract: There is provided an arithmetic operation device which is connected to a plurality of electronic control units. One or more electronic control units of the plurality of electronic control units constitute each of functions.

Abstract: Provided is a driving evaluation device that enables evaluation of driving for the purpose of improving a driving time in a circuit racecourse. The driving evaluation device includes an evaluation section extractor 24 that detects a deceleration section and an acceleration section in cornering, a tire friction circle-load factor calculator 27 that calculates, based on a front-rear acceleration and a lateral acceleration, a tire friction circle and a tire load factor in the deceleration section and those in the acceleration section, and a skill deficiency evaluator 28 that evaluates driving based on the tire friction circle and the tire load factor in the deceleration section and those in the acceleration section.

Abstract: A method for situation-based processing of sensor data from a motor vehicle. Sensor data generated by sensors relating to the situation in the surroundings of the motor vehicle is transferred to a processing unit via a bus. The processing unit takes into account the transferred sensor data to determine an information requirement, and generates a request for additional sensor data on the basis of the determined information requirement and the load on the bus, and sends this request to the sensors. A corresponding device is also described.