Abstract: A user's emotion can be determined based on pupil dilation response to a challenge prompt. In response to an authentication request, a registered challenge prompt and an expected pupil dilation response can be retrieved. The challenge prompt can include one or more images or a video designed to cause a pupil dilation response in a user. The challenge prompt is displayed to the user and the user's pupil dilation response is captured. At least one user action of the user is monitored and an emotion is determined based on the at least one user action. The emotion is associated with the pupil dilation response.

Abstract: Systems and methods for managing visual allocation are provided herein that use models to determine states based on visual data and, based thereon, output feedback based on the determined states. Visual data is initially obtained by a visual allocation management system. The visual data includes eye image sequences of a person in a particular state, such as engaging in a task or activity. Visual features can be identified from the visual data, such that glance information including direction and duration can be calculated. The visual data, information derived therefrom, and/or other contextual data is input into the models, which correspond to states, to calculate probabilities that the particular state that the person is engaged in is one of the modeled states. Based on the state identified as having the highest probability, an optimal feedback, such as a warning or instruction, can be output to a connected devices, systems, or objects.

Abstract: Methods for vehicle data collection by image analysis are provided. An example method involves positioning a camera in a vehicle to be pointed toward a field of interest in the vehicle, capturing an image of the field of interest with the camera, identifying a region of interest in the image that is expected to convey vehicle information, and running an image processing model over the region of interest to extract vehicle information from the image.

Abstract: Methods, systems, and computer readable mediums for determining a scene representation for a vehicle are provided. A disclosed method includes acquiring data from one or more sensors of the vehicle. The method further includes detecting, using processing circuitry, one or more objects in a surrounding of the vehicle based on the acquired data; determining whether an object of the detected one or more objects intersects with a vehicle lane of travel; determining whether the object is in a lane of travel of the vehicle; determining inter-vehicle gaps and cut-ins between the object and the vehicle; and rendering a scene representation including the inter-vehicle gaps and cut-ins between the object and the vehicle.

Abstract: Systems and methods are provided for navigating a host vehicle. In an embodiment, a processing device may be configured to receive a captured image acquired by a camera onboard the host vehicle; provide the captured image to an analysis module configured to generate an output including an indicator of a contact position of the occluded pedestrian with the ground surface, the analysis module including a trained model trained based a plurality of training images having been modified to occlude a region where a training pedestrian contacts a training ground surface; receive from the analysis module the generated output, including the indicator of the contact position of the occluded pedestrian with the ground surface; and cause at least one navigational action by the host vehicle based on the indicator of the contact position of the occluded pedestrian with the ground surface.

Abstract: An autonomous vehicle includes first and second road surface image obtaining devices that are located on a bottom surface of the vehicle body and obtain images of a road surface below the vehicle body, respectively. The autonomous vehicle also includes a memory unit that stores a map image of the road surface, the map image being associated with geographical location information. The autonomous vehicle further includes first and second self-location estimating units that each compare a feature extracted from the image of the road surface obtained by corresponding one of the first and second road surface image obtaining devices with a feature extracted from the map image, thereby estimating a self-location of the autonomous vehicle.

Abstract: A system and method is disclosed for capturing images of one or more moving vehicles (i.e., a target vehicle) from another moving vehicle (i.e., subject vehicle). The disclosed system dynamically adjusts illumination power, exposure times, and/or other settings to optimize image capture that takes into account distance and speed. By optimizing for distances and moving vehicles, the disclosed system improves the probability of capturing a legible, usable photographic image. In one example, the disclosed system may be incorporated into an asymmetric license plate reading (ALPR) system.

Abstract: An autonomous vehicle system removes ephemeral points from lidar samples. The system receives a plurality of light detection and ranging (lidar) samples captured by a lidar sensor. Along with the lidar samples, the system receives an aligned pose and an unwinding transform for each of the lidar samples. The system determines one or more occupied voxel cells in a three-dimensional (3D) space using the lidar samples, their aligned poses, and their unwinding transforms. The system identifies occupied voxel cells representative of noise associated with motion of an object relative to the lidar sensor. The system filters the occupied voxel cells by removing the cells representative of noise. The system inputs the filtered occupied voxel cells in a 3D map comprising voxel cells, e.g., during the map generation and/or a map update.

Abstract: Aspects of the disclosure relate to detecting an emergency vehicle. For instance, a plurality of images may be taken from a perspective of an autonomous vehicle. One or more gates representing a region of interest at a respective distance from the vehicle may be generated for the images. A plurality of lights may be detected within the one or more gates. A first candidate emergency vehicle may be identified from a detected plurality of lights in one or more gates of one of the images, and a second candidate emergency vehicle may be identified from a detected plurality of lights in one or more gates of another of the images. The first and second candidate emergency vehicles are determined to be the same emergency vehicle and to be active. An operational system of the autonomous vehicle is controlled based on the determination that the given emergency vehicle is active.

Abstract: An autonomous driving control system and a method thereof are provided. The autonomous driving control system includes a strategy performing device that generates and performs a stop strategy of a vehicle on the basis of a target stop location, when a critical situation occurs during autonomous driving, a behavior controller that controls a behavior of the vehicle depending on the stop strategy, and an emergency module controller that runs a predetermined emergency module, when the critical situation occurs.

Abstract: A vehicle cleaner system includes: a cleaner unit configured to be mounted on a vehicle and to discharge a cleaning medium to an external sensor that acquires information outside the vehicle so as to clean the external sensor; and a cleaner control unit configured to control the cleaner unit. The cleaner control unit is configured to acquire weather information, and control the cleaner unit such that at least one of a type of the cleaning medium, a discharge amount of the cleaning medium, the number of times of discharge of the cleaning medium, the number of times of discharge of the cleaning medium per unit time, and a discharge time of the cleaning medium varies according to the weather information.

Abstract: A system and method are provided, wherein the system includes a traffic control signal, a wireless interface, a mast, a support base, a wireless control device, and a base station for communicating between the wireless interface and the wireless control device. The method involves receiving input from the wireless control device, generating a control signal for operating the traffic control signals, and transmitting the control signal to the traffic control signals.

Abstract: A method and apparatus for determining a part for a vehicle. The vehicle's vehicle identification number is determined, and the vehicle's manufacture information is determined. A specific part for the particular vehicle is identified. Whether a part code zone for the part exists on a vehicle identification label (VIN Label) is determined. If the part code zone exists on the VIN Label, then a zonal optical character recognition procedure is performed on the VIN Label and a part code in the part code zone is extracted. Or if the part code zone does not exist on the VIN Label, then a list of parts for the vehicle is determined based on the vehicle's manufacture information and the part is selected from the list of parts.

Abstract: A mobile device configured to perform gesture recognition for a vehicle information and/or entertainment system comprises a depth camera; an orientation sensor; and a processor configured to detect one or more gestures from images captured by the depth camera according to a gesture detection algorithm; in which the processor is configured to vary the gesture detection algorithm in dependence upon an orientation of the mobile device detected by the orientation sensor.

Abstract: Disclosed herein is a handheld speed gun incorporating automatic number plate recognition (ANPR) functionality. As the image size of a vehicle license plate varies depending on its distance from the speed gun, in the present invention the distance to the target vehicle is known through the functionality of the laser sensor so the size of the pixels for the number plate can be estimated. Since the image of the number plate may be tilted in a handheld device, the present invention compensates for this by use of the instrument's tilt sensor or through other compensation by use of the image itself.

Abstract: The invention relates to a method for supporting an advanced driver assistance system in a motor vehicle, comprising the following steps: providing a map, wherein categorized objects are stored in associated positions in the map, capturing environment data using at least one environment sensor system of the advanced driver assistance system, analyzing the captured environment data using an analysis apparatus of the advanced driver assistance system, wherein the captured environment data are analyzed for object recognition according to the categorized objects stored in the map. Furthermore, the invention relates to an associated device.

Abstract: The present disclosure provides a target tracking method to be executed by a computing device, including: generating an optical flow image in accordance with a series of event data from a dynamic vision sensor, each event being triggered by movement of a target object relative to the dynamic vision sensor; determining a movement speed and a movement direction of at least one target object in a current image frame in accordance with the optical flow image; predicting a position of a corresponding target object in a next image frame in accordance with the movement direction and the movement speed; and when a predicted position is within a range of a field of view, taking the corresponding target object as a to-be-tracked target. The present disclosure further provides a computing device.

Abstract: A driver monitoring system includes at least two cameras configured to record images of a driver within a cabin of a vehicle. A first camera is disposed on a driver side of the cabin and a second camera is disposed on a passenger side of the cabin. At least one of the at least two cameras is disposed in a mirror replacement display or in a mirror replacement display location. A controller is in communication with the at least two cameras and is configured to determine a pose of the driver based on images from the at least two cameras. At least one of the images originates from at least one of the first camera and the second camera.

Abstract: An ego vehicle includes decider modules and a grader module coupled to a resolver module. The decider modules generate trajectory decisions at a current time, generate a current two-dimensional slice of a flat space around the ego vehicle, generate future two-dimensional slices of the flat space by projecting the current two-dimensional slice of the flat space forward in time, and generate a three-dimensional state space by stacking the current two-dimensional slice and the future two-dimensional slices. The grader module generates rewards for the trajectory decisions based on a recent behavior of an ego vehicle. The resolver module selects a final trajectory decision for the ego vehicle from the trajectory decisions based on the three-dimensional state space and the rewards. The current two-dimensional slice includes a current ego vehicle location and current neighboring vehicle locations. The future two-dimensional slices include future ego vehicle locations and future neighboring vehicle locations.

Abstract: A method, apparatus, and computer program product are provided for identifying on-street parking from aerial imagery. A method may include: receiving an aerial image of a geographic region; applying an object detection algorithm to the received aerial image to identify vehicle objects within the aerial image; identifying one or more clusters of vehicle objects within the aerial image; generating cluster lines for the one or more clusters of vehicle objects; map matching the cluster lines for the one or more clusters of vehicle objects to a map of the geographic region; and identifying on-street parking for a road segment in response to a cluster line of the cluster lines for the one or more clusters of vehicle objects satisfying predetermined criteria with respect to the road segment.

Abstract: Embodiments include systems and methods executed by a processor of a vehicle for presenting relevant warnings to a vehicle operator, including receiving a vehicle-to-everything (V2X) communication including information regarding a V2X-identified threat, determining whether the vehicle operator has not recognized the V2X-identified threat, determining a display location that is most likely to receive the vehicle operator's attention in response to determining that the vehicle operator has not recognized the V2X-identified threat, and generating an alert regarding the V2X-identified threat on the determined display location. The generated alert regarding the V2X-identified threat on the determined display location may exclude alerts regarding any threat conditions that the processor has determined that the vehicle operator has recognized.

Abstract: A method for matching a reference object and a test object includes providing a test object in a field of sensing of at least one sensor disposed at a vehicle. A volume match is determined based on a volume of the reference object and a volume of the test object. A distance match is determined based on a center and orientation of the reference object and a center and orientation of the test object. An angle match is determined based on a yaw angle of the reference object and a yaw angle of the test object. A superposition of the volume match, the distance match, and the angle match is determined based on a multiplication of the volume match, the distance match, and the angle match. A degree of matching of the reference object and the test object is determined based on the superposition.

Abstract: An apparatus for recognizing a face is provided. The apparatus includes a camera configured to obtain a partial-face image of a passenger, and a controller configured to learn a boarding condition of a user and recognize the user based on the partial-face image of the passenger when a current boarding condition of the passenger satisfies the learned boarding condition.

Abstract: A laser radar device includes a laser radar optical system that emits laser light and receives reflected light of the laser light reflected from a reflector disposed outside the laser radar device. A controller determines that it is rainy weather when a measurement width of the reflector in a scanning direction of the laser light measured by use of the laser light and the reflected light is larger than a predetermined reference measurement width of the reflector.

Abstract: This disclosure describes techniques to detect an object. The techniques include operations comprising: receiving an image captured by overhead camera; identifying a region of interest (ROI) of a plurality of regions within the image; selecting an object classifier from a plurality of object classifiers based on a position of the identified ROI relative to the overhead camera; and applying the selected object classifier to the identified ROI; and detecting presence of the object within the ROI in response to applying the selected object classifier to the identified ROI.

Abstract: The present invention relates to the determination of damage to portions of a vehicle. More particularly, the present invention relates to determining whether each part of a vehicle should be classified as damaged or undamaged and optionally the severity of the damage to each part of the damaged vehicle. Aspects and/or embodiments seek to provide a computer-implemented method for determining damage states of each part of a damaged vehicle, indicating whether each part of the vehicle is damaged or undamaged and optionally the severity of the damage to each part of the damaged vehicle, using images of the damage to the vehicle and trained models to assess the damage indicated in the images of the damaged vehicle.

Abstract: A first image is obtained prior to a second image. Upon dividing the second image into a plurality of zones, light characteristic values for each of the plurality of zones are determined based on at least one of a brightness value, a contrast value, and an intensity value for the respective zones. A first difference score for one of the zones is determined based on a difference between corresponding light characteristic values for the one zone in the first and second images. Upon identifying an object in the one zone of the first and second images, a second difference score for the one zone is determined based on determining a difference between respective confidence scores associated with the corresponding identified objects. Upon determining at least one of the first or second difference score is greater than a respective threshold, the vehicle is operated based on the first image.

Abstract: An adaptive processing method for new scenes in autonomous driving, comprising: obtaining scene data corresponding to new scene of vehicle driving, wherein the scene data describes vehicles state and driving operations in the new scene; obtaining a test set of the new scene based on processing the scene data by a preset distribution; updating parameters of a pre-training model by inputting the test set, and obtaining a scene model adapted to the new scene based on gradient iteration of general model parameters of the pre-training model, wherein the scene model is configured to output an autonomous driving strategy for the vehicle in the new scene. Therefore, the autonomous driving vehicle transforms a new scene to a known scene, and no longer be troubled by unpredictable new scenes, and greatly enhance the reliability and stability of autonomous driving.

Abstract: A method, non-transitory computer readable medium, and system for receiving sensor data from one or more sensors disposed on an autonomous vehicle, determining whether a potentially dangerous event is detected in the environment around the autonomous vehicle, and providing automatically at least a portion of the sensor data to a user associated with the autonomous vehicle. The sensor data may comprise measurements associated with an environment around the autonomous vehicle. The determination of the potentially dangerous event may be based on the sensor data. The portion of the sensor data may be provided automatically in response to determining that the potentially dangerous event is detected.

Abstract: A display device includes an electronic control unit configured to: obtain a traveling plan from an automatic driving system of a vehicle, the traveling plan including a course of the vehicle under automatic drive control of the automatic driving system; obtain, from the automatic driving system, a system confidence level of the automatic drive control calculated based on at least an external environment around the vehicle; and display, on a display, a pointer as an image indicating the course during the automatic drive control in a display mode set based on the system confidence level.

Abstract: An object of the present invention is to more appropriately extrapolate a sign of a state that may affect a movement of a user. A state extrapolation device according to the present invention includes a vital sign acquisition unit that acquires a vital sign of a user, and a sign detection unit that uses a learned model that has learned, as training data, sign data about the vital sign related to a predetermined physical condition abnormality, and detects a sign by determining whether or not the vital sign of the user corresponds to a sign of the predetermined physical condition abnormality.

Abstract: A door opening control apparatus and a door opening control method thereof are provided. The door opening control apparatus includes a recognizer configured to recognize a surrounding obstacle based on sensor recognition information received from a plurality of sensors, a determiner configured to calculate a maximum opening angle of a door for preventing collision with the recognized surrounding obstacle and to determine a risk of collision between the door and the surrounding obstacle based on the calculated maximum opening angle, and a controller configured to control an opening angle of the door to prevent the door from colliding with the surrounding obstacle when determining that the risk of collision is present.

Abstract: Various embodiments for managing assets in a data center device rack include: establishing a data connection between a cabinet level controller and at least one primary power distribution unit (PDU); using a first electrical outlet on the primary PDU to establish an electrical connection between the primary PDU an electrical asset in a data center equipment rack; using a first asset interface connector on the cabinet level controller to establish a data connection between the cabinet level controller and the electrical asset in the data center equipment rack, the first electrical outlet and the first asset interface connector being in horizontal alignment; using a router integrated into the cabinet level controller to connect the cabinet level controller to a wide area Internet Protocol (IP) network; and using the router to establish a single IP address corresponding to a plurality of electrical assets in the data center equipment rack.

Abstract: Techniques for determining predictions on a top-down representation of an environment based on vehicle action(s) are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) can capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle or a pedestrian). A multi-channel image representing a top-down view of the object(s) and the environment can be generated based on the sensor data, map data, and/or action data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) can be encoded in the image. Action data can represent a target lane, trajectory, etc. of the first vehicle. Multiple images can be generated representing the environment over time and input into a prediction system configured to output prediction probabilities associated with possible locations of the object(s) in the future, which may be based on the actions of the autonomous vehicle.

Abstract: An occupancy grid manager having a non-uniform occupancy which includes a plurality of cells, configurable in a plurality of cell sizes, each cell representing a region of an environment of a vehicle; and one or more processors, configured to determine one or more context factors; select a cell size for a cell of the plurality of cells based on the one or more context factors; process sensor data provided by one or more sensors; and determine a probability that the cell of the plurality of cells is occupied based on the sensor data.

Abstract: The driving support system includes an imaging section installed to a vehicle capable of executing a driving support state, and the imaging section being capable of imaging a imaging subject positioned in surroundings of the vehicle, and a processor connected to the imaging section. The processor is configured to generate image data, determine whether or not a predetermined recording condition has been satisfied, cause the image data to be recorded in the memory in cases in which the recording condition has been determined to have been satisfied, determine whether or not the vehicle is in any of the driving support states, and change the recording condition to a specific recording condition that is the recording condition corresponding to the driving support state of the vehicle in cases in which the vehicle has been determined to be in any of the driving support states.

Abstract: Point cloud data relating to a matching target is efficiently eliminated after completion of a process of matching between sets of point cloud data obtained at different viewpoints. The surveying data processing device includes a target detecting unit, a location acquiring unit, a point cloud data eliminating region setting unit, and a point cloud data eliminating unit. The target detecting unit detects a target in point cloud data. The point cloud data is obtained by emitting laser light on an object having the target and by detecting the light reflected back from the object. The target location acquiring unit acquires a location of the detected target. The point cloud data eliminating region setting unit sets a point cloud data eliminating region containing the target, based on the location of the target. The point cloud data eliminating unit eliminates point cloud data contained in the point cloud data eliminating region.

Abstract: A method for testing a vehicular driving assist system includes providing a neural network and training the neural network using a database of images, with each image of the database of images including an image of a headlight or a taillight of a vehicle. The trained neural network is provided with an input image that does not include a headlight or a taillight. The neural network, using the input image, generates an output image, with the output image including an image of a headlight or taillight generated by the neural network. The output image is provided as an input to the driving assist system to test the driving assist system.

Abstract: Systems and methods are provided for detecting a flashing light on one or more traffic signal devices. The method includes capturing a series of images of one or more traffic signal elements in a traffic signal device over a length of time. The method further includes, for each traffic signal element, analyzing the series of images to determine one or more time periods at which the traffic signal element is in an on state or an off state, and analyzing the time periods to determine one or more distinct on states and one or more distinct off states. The method further includes identifying one or more cycles correlating to a distinct on state immediately followed by a distinct off state, or a distinct off state immediately followed by a distinct on state, and, upon identifying a threshold number adjacent cycles, classifying the traffic signal element as a flashing light.

Abstract: Methods for performing operations for improving driver safety across a fleet of vehicles are disclosed. A plurality of safety events pertaining to a driving of a fleet of vehicles by a plurality of drivers are detected. A subset of the events is identified. The subset corresponds to one or more safety events of the plurality of safety events involving one or more vehicles of the fleet of vehicles to which drivers have not been assigned. A user interface is generated for presentation on a client device, the user interface including an interactive user interface element for accessing the subset of the events. One or more user interface elements are provided for accepting or rejecting recommendations for assignments of one of the plurality of drivers to each of the vehicles. The recommendations are generated based on an application of a machine-learned model to images of faces captured.

Abstract: A method for controlling a vehicle to make an emergency stop of the vehicle providing a camera and an electronic control unit (ECU) at the vehicle. Presence of a road condition is determined at the road along which the vehicle is traveling. Responsive to determining an emergency driving condition while the vehicle is traveling along the road at the road condition, the ECU at least partially controls driving of the vehicle along the road. While the ECU is at least partially controlling driving of the vehicle along the road, and responsive to determining an end of the road condition, a target stopping location is determined ahead of the vehicle at the road along which the vehicle is traveling and after the end of the road condition. The ECU at least partially controls driving of the vehicle to the target stopping location.

Abstract: To determine diverting availability of a trained recognition model of another object to a target object. A system includes one or more processors and one or more storage devices. The one or more storage devices store an image time series including a target object, and a trained object recognition model for one or more objects which are different from the target object. The one or more processors acquire a movement trajectory of the target object from a recognition result of the target object in the image time series by the object recognition model, and determine diverting availability of the object recognition model to the target object based on the movement trajectory of the target object.

Abstract: An entertainment system for a vehicle, the system including: a sound emitting module including multiple sound emitting units, wherein the sound emitting module is adapted to be arranged such that the multiple sound emitting units are distributed along the transverse extension of a windshield of the vehicle and to emit sound towards the windshield, and a display device arranged between the sound emitting module and an occupant seating position, wherein the display device is arranged to cover the sound emitting module as seen from the occupant seating position. The disclosed entertainment system provides the advantage of integrating a more advanced sound system in the form of a sound emitting module including multiple sound emitting units.

Abstract: The present application discloses a method and apparatus for extracting a geographic location point spatial relationship, and relates to the field of big data technologies. A specific implementation solution is as follows: determining geographic location point pairs included in real-scene images by performing signboard recognition on the real-scene images collected by terminal devices; acquiring at least two real-scene images collected by the same terminal device and including the same geographic location point pair; and determining a spatial relationship of the same geographic location point pair by using shooting parameters of the at least two real-scene images. The geographic location point spatial relationship extracted through the present application has higher accuracy and a coverage rate.

Abstract: Methods and systems for crowd level estimation are provided. The system for crowd level estimation includes an input module and a crowd level estimation module. The input module receives an input image of a crowd and the crowd level estimation module estimates a crowd level of the crowd in the input image in response to a crowd density level.

Abstract: An image processor includes an imaging device that captures an image of a road surface around a vehicle V, and a control portion that detects a marker drawn on the road surface from the captured image. The control portion connects a plurality of broken markers to create a single marker when the detected marker is broken into plural.

Abstract: A digital camera and a method for aligning digital images comprising: receiving images including first and second images depicting a first and a second region of a scene, the regions being overlapping and displaced along a first direction; aligning the images using a transformation; determining disparity values for an overlap between the images; identifying misalignments by identifying blocks of pixels in the first image having a same position along a second direction and having disparity values exhibiting a variability lower than a first threshold and exhibiting an average higher than a second threshold; adjusting the transformation for the identified blocks of pixels in the first image and their matching blocks of pixels in the second image; and realigning the images using the adjusted transformation.

Abstract: A system for providing traffic information to a driver of an ego vehicle includes at least one sensor that provides image data of detected objects, including other vehicles, in a surrounding area of the ego vehicle; a position detection device that detects a position of the ego vehicle; a display unit that renders visual information relating to an environmental model of the surrounding area of the ego vehicle, the position, and corresponding digital map data; and an image analysis unit configured to determine a vehicle characteristic of at least one other vehicle in the surrounding area of the ego vehicle from a vehicle image of the at least one other vehicle generated based on the image data from the at least one sensor and to display information on the display unit based on the determined vehicle characteristic.

Abstract: A vehicle includes a light switch for manually operating a lighting state of a lighting device. The light switch includes a light-off position and an auto-light position for executing an auto-light process. A vehicle control system includes a first controller for executing an automated driving of the vehicle, and a second controller for controlling a lighting state of the lighting device based on a request from the first controller or operation information of the light switch. The first controller is configured to transmit an auto-light request for executing the auto-light process to the second controller during execution of the automated driving. The second controller is configured to execute the auto-light process when the auto-light request is received from the first controller in a state where the light switch is operated to the light-off position.

Abstract: Disclosed is a feedback adversarial learning framework, a recurrent framework for generative adversarial networks that can be widely adapted to not only stabilize training but also generate higher quality images. In some aspects, a discriminator's spatial outputs are distilled to improve generation quality. The disclosed embodiments model the discriminator into the generator, and the generator learns from its mistakes over time. In some aspects, a discriminator architecture encourages the model to be locally and globally consistent.