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 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: 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: 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: 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: 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: 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: 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: 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: 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.

Abstract: A method, a system, and a computer program product may be provided for generating map data associated with one or more objects in a region. The method includes receiving point cloud data associated with the region. The method further includes generating a georeferenced top down raster image of the region, based on the point cloud data. The georeferenced top down raster image is indicative of a top surface of each of the one or more objects. The method further includes determining boundary data of the top surface of each of the one or more objects, based on the georeferenced top down raster image and generating the map data associated with the one or more objects, based on the boundary data of the top surface of each of the one or more objects.

Abstract: The present application discloses an improved transportation matching system, and corresponding methods and computer-readable media. According to the disclosed embodiments, the transportation matching system utilizes an image-based transportation request interface and environmental digital image stream to efficiently generate transportation requests with accurate pickup locations. For instance, the disclosed system can utilize one or more environmental digital images provided from a requestor computing device (e.g., a mobile device or an augmented reality wearable device) to determine information such as the location of the requestor computing device and a transportation pickup location within the environmental digital images. Furthermore, the disclosed system can provide, for display on the requestor computing device, one or more augmented reality elements at the transportation pickup location within an environmental scene that includes the transportation pickup location.

Abstract: In one aspect, a system for controlling the operation of a seed-planting implement may include a furrow-forming tool configured to form a furrow in soil present within a field. Furthermore, the system may include a sensor configured to capture data indicative of a topographical profile of the soil within the field. Additionally, a controller of the disclosed system may be configured to identify a topographical feature within the field based on the data received from the sensor. Furthermore, the controller may be configured to determine a position of the furrow-forming tool relative to the identified topographical feature. Additionally, the controller may be configured to initiate a control action to adjust the position of the furrow-forming tool when it is determined that the relative position between the furrow-forming tool and the identified topographical feature is offset from a predetermined positional relationship defined for the furrow-forming tool.

Abstract: A system and a method for face recognition are disclosed. The system also includes an image capturing subsystem configured to capture one or more images of faces. The system also includes a feature extraction subsystem configured to extract one or more features from the one or more images of faces. The system also includes a feature comparison subsystem configured to compare the one or more extracted features in a local database. The system also includes a feature transmission subsystem configured to transmit the one or more images and one or more extracted features to a remote server. The feature transmission subsystem is also configured to compare the one or more transmitted features to the one or more features pre-stored in the remote server. The system also includes a feature regeneration subsystem configured to regenerate the one or more matched features in the local database from the remote server.

Abstract: Systems and methods for using image analysis techniques to assess unsafe driving conditions by a vehicle operator are discloses. According to aspects, a computing device may access and analyze image data depicting the vehicle operator. In analyzing the image, the computing device may measure certain visible metrics as depicted in the image data and compare the metrics to corresponding threshold values, and may accordingly determine whether the vehicle operator is exhibiting an unsafe driving condition. The computing device may generate and present alerts that indicate any determined unsafe driving condition.

Abstract: Methods for image-based detection of the tops of sample tubes used in an automated diagnostic analysis system may be based on a convolutional neural network to pre-process images of the sample tube tops to intensify the tube top circle edges while suppressing the edge response from other objects that may appear in the image. Edge maps generated by the methods may be used for various image-based sample tube analyses, categorizations, and/or characterizations of the sample tubes to control a robot in relationship to the sample tubes. Image processing and control apparatus configured to carry out the methods are also described, as are other aspects.

Abstract: An electrical device controller includes a processor, and a memory for storing a program executed by the processor. The processor controls the electrical device in multiple operation modes including an automatic mode which automatically changes the operation state of the electrical device and a stop mode which stops the electrical device, controls the electrical device in an operation mode specified with an operating member operated by an occupant when the vehicle is manually driven, controls the operation state of the electrical device in the automatic mode regardless of the operation mode specified with the operating member when the vehicle is autonomously driven, and sets the operation mode of the electrical device at least temporarily to the stop mode when the operation mode specified with the operation member is switched to the stop mode from an operation mode other than the stop mode, when the vehicle is autonomously driven.

Abstract: Systems and methods of processing crowdsourced navigation information for use in autonomous vehicle navigation are disclosed. A method may include processing, by a mapping server, crowdsourced navigation information from a plurality of vehicles obtained by sensors coupled to the plurality of vehicles, wherein the navigation information describes road lanes of a road segment; collecting data about landmarks identified proximate to the road segment, the landmarking including a traffic sign; generating, by the mapping server, an autonomous vehicle map for the road segment, wherein the autonomous vehicle map includes a spline corresponding to a lane in the road segment and the landmarks identified proximate to the road segment; and distributing, by the mapping server, the autonomous vehicle map to an autonomous vehicle for use in autonomous navigation over the road segment.

Abstract: In one embodiment, a method includes receiving an image of an object captured in a geographic location. The method includes determining the geographic location associated with the image. The geographic location is represented in a map that includes one or more ambient light measurements corresponding to one or more geographic locations. The method includes using the one or more ambient light measurements corresponding to the geographic location in the map associated with the image to generate a color corrected image. The method includes determining a classification of the object using the color corrected image.

Abstract: According to an aspect of an embodiment, operations may comprise obtaining a first point cloud that includes a first point. The operations also comprises obtaining a second point cloud that is a copy of the first point cloud and that includes a second point that is a copy of the first point. The operations also comprises moving the second point cloud with respect to the first point cloud according to a first vector. The operations also comprises identifying a closest point of the first point cloud that is closest to the second point of the second point cloud. The operations also comprises determining a second vector between the closest point and the second point. The operations also comprises determining a measure of usefulness of the first point based on the first vector and the second vector. The operations also comprises indicating the measure of usefulness of the first point.

Abstract: An apparatus includes a front detection sensor detecting presence of a pedestrian on a driving lane of the vehicle, gaze information of the pedestrian, and a distance and a relative speed between the pedestrian and the vehicle; a vehicle sensor detecting at least one of a speed, an acceleration, a steering angle, a steering angular velocity, or a pressure of a master cylinder of the vehicle; an electronic control unit activating a function of a pedestrian detection and collision mitigation system based on information detected by the front detection sensor and the vehicle sensor; and a warning unit operated to inform a driver of a collision of the pedestrian with the vehicle by controlling the electronic control unit.

Abstract: A trailer having a kingpin or having a drawbar for coupling a tractor unit on a coupling side of the trailer, wherein the trailer has a detectable pattern on its coupling side, and a tractor unit for coupling to a kingpin or a drawbar of a trailer, wherein the tractor unit has, for the identification of a trailer and/or for assisting a coupling process, in particular on a coupling side of the drawbar, a detection unit for detecting a detectable pattern.

Abstract: A system for determining agricultural vehicle guidance quality includes an imaging device configured to capture image data depicting a plurality of crops rows present within a field as an agricultural vehicle travels across the field. Additionally, the system includes a controller communicatively coupled to the imaging device. As such, the controller configured to determine a guidance line for guiding the agricultural vehicle relative to the plurality of crop rows based on the captured image data. Furthermore, the controller is configured to determine a crop row boundary consistency parameter associated with one or more crop rows of the plurality of crop row present within a region of interest of the captured image data. Moreover, the controller is configured to determine a quality metric for the guidance line based on the crop row boundary consistency parameter.

Abstract: A method for a sensor-based and memory-based representation of a surroundings of a vehicle. The vehicle includes an imaging sensor for detecting the surroundings. The method includes: detecting a sequence of images; determining distance data on the basis of the detected images and/or of a distance sensor of the vehicle, the distance data comprising distances between the vehicle and objects in the surroundings of the vehicle; generating a three-dimensional structure of a surroundings model on the basis of the distance data; recognizing at least one object in the surroundings of the vehicle on the basis of the detected images, in particular by a neural network; loading a synthetic object model on the basis of the recognized object; adapting the generated three-dimensional structure of the surroundings model on the basis of the synthetic object model and on the basis of the distance data; and displaying the adapted surroundings model.

Abstract: A computer-implemented method for reliably identifying objects in a sequence of input images received with the aid of an imaging sensor, positions of light sources in the respective input image being ascertained from the input images in each case with the aid of a first machine learning system, in particular, an artificial neural network, and objects from the sequence of input images being identified from the resulting sequence of positions of light sources, in particular, with the aid of a second machine learning system, in particular, with the aid of an artificial neural network.

Abstract: In some examples, an unmanned aerial vehicle (UAV) employs one or more image sensors to capture images of a scan target and may use distance information from the images for determining respective locations in three-dimensional (3D) space of a plurality of points of a 3D model representative of a surface of the scan target. The UAV may compare a first image with a second image to determine a difference between a current frame of reference position for the UAV and an estimate of an actual frame of reference position for the UAV. Further, based at least on the difference, the UAV may determine, while the UAV is in flight, an update to the 3D model including at least one of an updated location of at least one point in the 3D model, or a location of a new point in the 3D model.

Abstract: System and techniques for vehicle environment modeling with a camera are described herein. A device for modeling an environment comprises: a hardware sensor interface to obtain a sequence of unrectified images representative of a road environment, the sequence of unrectified images including a first unrectified image, a previous unrectified image, and a previous-previous unrectified image; and processing circuitry to: provide the first unrectified image, the previous unrectified image, and the previous-previous unrectified image to an artificial neural network (ANN) to produce a three-dimensional structure of a scene; determine a selected homography; and apply the selected homography to the three-dimensional structure of the scene to create a model of the road environment.

Abstract: The present disclosure in some embodiments provides a method and apparatus which utilize a learning model based on deep learning for enabling a vehicle to autonomously estimate a road surface condition by using a deep learning-based learning model, determine a terrain mode optimized for the road surface being traveled by the vehicle, and control respective in-vehicle modules and thereby automatically control the terrain mode.

Abstract: This disclosure is generally directed to systems and methods for protecting the health of occupants of a vehicle. In an example method, a health monitoring apparatus in a vehicle evaluates an individual and detects a symptom of a contagious disease. The individual may be already seated in a first seat in the vehicle or intends to enter the vehicle. The health monitoring apparatus identifies a second seat that has a pre-defined spatial separation distance from the first seat. The pre-defined spatial separation distance can exceed a threshold spatial separation distance selected to provide health protection against the contagious disease. The health monitoring apparatus issues an advisory to the individual to occupy the second seat. In another example method, the health monitoring apparatus may adjust an airflow pattern in the vehicle so as to provide directional airflows to protect various occupants of the vehicle against an airborne contagious disease.

Abstract: Dimmable external vehicle lighting and methods of use are provided herein. An example method includes determining environmental light intensity around a vehicle, determining a luminance of an external light of the vehicle, determining a difference in magnitude between the environmental light intensity and the luminance of the external light, and selectively adjusting the luminance of the external light based on the difference.

Abstract: An intelligent robot cleaner setting a travel path based on a video learning includes a travel driver, a suction unit, an image acquisition unit, and a controller. The travel driver moves to an area to be cleaned along the travel path. The suction unit sucks foreign substances on the travel path. The image acquisition unit acquires an image on the travel path. The controller analyzes the image, decides whether an object is present on the travel path, classifies a type of the object, and sets a bypass travel path that avoids the object if the object is an avoidance object.

Abstract: A disclosed example includes: a resource utilization analyzer to determine 1) first workloads of a first workload type deployed in a first server room in a data center, and 2) second workloads of a second workload type deployed in the first server room; a workload authorizer to determine that first virtual machines executing the first workloads and second virtual machines executing the second workloads cause a first server rack to generate an amount of heat; and a migrator to migrate the first virtual machines from the first server rack of the first server room to a second server rack of a second server room in the data center to reduce a temperature in the first server room based on the amount of heat, the migrator to migrate the first virtual machines to the second server rack without migrating the second virtual machines to the second server rack.

Abstract: Embodiments of the present disclosure are directed to lane marker prediction for occluded lane markers. Image data from one or more sensors of a vehicle is received by a processor of a control system. The image data includes a roadway from a route being navigated by the vehicle and lane marker information. If there are not enough lane markers captured in the lane marker information to produce a threshold look-ahead horizon of the roadway ahead of the vehicle, a longest lane marker ahead of the vehicle from the lane marker information is selected. A curvature tangent to the longest lane marker is computed and predictive lane markers are generated based on the curvature tangent. The vehicle is steered based on the predictive lane markers ahead of the vehicle generated from the curvature tangent.

Abstract: Provided herein is a headlamp assembly comprising a housing that encloses: a sensor that acquires data associated with a surrounding environment; a light source that illuminates a field of view comprising a portion of the surrounding environment; and one or more processors that analyze the acquired data and determine a direction, field of view, power, or an intensity of the illumination of the portion based on the analyzed data.

Abstract: Methods for improving compliance with regulations pertaining to vehicle driving records are disclosed. One or more digital images from a camera mounted in a vehicle are received. Based on a determination that the vehicle has hours of service that have not been assigned to a driver, a subset of the one or more digital images corresponding to the hours of service are identified based on the timestamps. The subset of the one or more digital images are processed to identify a correspondence between a face of a person included in the one or more digital images and a face of a known person. Based on the correspondence transgressing a threshold level of correspondence, a user interface is generated for presentation on a device. The user interface includes an interactive user interface element for accepting a recommendation to assign the known person as the driver for the unassigned hours of service.

Abstract: Systems and methods for the detection and analysis of road markings and other road objects are described. A method for detection of road markings comprises identifying image data including lane markings associated with a road segment, defining a plurality of subsections for the road segment, identifying boundary recognition observations for the lane markings from the image data corresponding to the at least one of the plurality of subsections for the road segments, calculating one or more clusters for the boundary recognition observations according to color or intensity, and outputting a lane marking indicator indicating the color or the intensity, for the at least one of the plurality of subsections for the road segments, in response to the one or more clusters.

Abstract: Systems and methods for operating an autonomous vehicle. The methods comprising: obtaining, by a computing device, loose-fit cuboids overlaid on 3D graphs so as to each encompass LiDAR data points associated with a given object; defining, by the computing device, an amodal cuboid based on the loose-fit cuboids; using, by the computing device, the amodal cuboid to train a machine learning algorithm to detect objects of a given class using sensor data generated by sensors of the autonomous vehicle or another vehicle; and causing, by the computing device, operations of the autonomous vehicle to be controlled using the machine learning algorithm.

Abstract: A method of controlling a vehicle using a first model trained according to optimized output of a second model.

Abstract: A vehicular vision system includes first and second cameras disposed at a vehicle and having respective overlapping fields of view that include a road surface of a road along which the vehicle is traveling. Image data captured by the cameras is provided to an image processor and is processed to determine relative movement of a road feature present in the captured image data. The determined movement of the road feature relative to the vehicle in first image data captured by the first camera is compared to the determined movement of the road feature relative to the vehicle in second image data captured by the second camera, and at least a rotational offset of the second camera at the vehicle relative to the first camera at the vehicle is determined and the image data are remapped to at least partially accommodate misalignment of the second camera relative to the first camera.