Abstract: A method to be implemented by a computer system includes: transforming each of training images into a respective transformed training image; calculating a classification loss value based on detection results that are acquired from parking status prediction results obtained by performing feature extraction on the transformed training images; and adjusting candidate spatial transforming parameters, candidate feature extraction parameters and candidate logistic regression parameters when it is determined that a combination of the aforementioned parameters is not optimal based on the classification loss value, followed by repeating above-mentioned steps using the adjusted parameters.

Abstract: A vehicular control system includes a forward viewing camera disposed at an in-cabin side of a windshield of a vehicle and viewing forward of the vehicle. Road curvature of a road along which the vehicle is traveling is determined responsive at least in part to processing by an image processor of image data captured by the camera. Responsive at least in part to processing of captured image data, a traffic lane of the road along which the vehicle is traveling is determined. Responsive at least in part to processing of captured image data, another vehicle present on the road and forward of the vehicle may be detected. Responsive at least in part to processing of captured image data, the system may determine that the detected other vehicle is travelling in a traffic lane to the left or to the right of the traffic lane along which the vehicle is traveling.

Abstract: Disclosed are a camera and an object processing apparatus using the same. A camera according to an embodiment of the present invention focuses on moving objects by adjusting the ray distance between a lens and a sensor in a manner whereby a mirror is moved between the lens and the sensor, which are each fixedly installed, or whereby one side end of the sensor is moved, without a mirror.

Abstract: A device for controlling a headlight of a vehicle is configured to receive images consecutively captured by a camera, the images showing an area in front of a vehicle, detect a road in one of the images, divide the road detected in the image in segments, track the segments over time in the images, determine at least one feature related to the brightness for each of the segments, determine from the features related to the brightness of the segments whether preceding and/or oncoming traffic exists, and generate a control signal for controlling a headlight of the vehicle if preceding and/or oncoming traffic exists.

Abstract: Implementations for optical character recognition of a language script can include actions of receiving an image comprising a graphical representation of a word written in the language script, segmenting the word into two or more segments, each segment being determined based on one or more of a variation in a height of the word and a variation in a width of the word, and including at least one character, providing a boundary for each segment of the two or more segments, the boundary enclosing the at least one character of a respective segment, each boundary having an edge with respect to an axis of the image, normalizing boundaries of the two or more segments by aligning edges of the boundaries, and labeling each segment of the two or more segments with a respective label, the respective label indicating a language character within the respective boundary.

Abstract: It is an object of the present invention to provide a predictive traffic law enforcement profiler apparatus and method which incorporates a means to determine current location, time, velocity and also incorporates a means to utilize a database derived from historic traffic law enforcement records, crowd sourced records and historical traffic data and also incorporates a predictive processing means to provide historic traffic law enforcement records and estimates of enforced speed limits and enforcement profiles, patrol locations and schedules of traffic law enforcement to a driver.

Abstract: A first measuring device measures a location of its own vehicle relative to each feature point on a surrounding structure around a road surface on which the vehicle. A first feature-point is provided which, based on output from the first measuring device, acquires coordinates of the each feature point expressed in a coordinate system of the first measuring device, and uses a self-location to convert the coordinates into an external coordinate. A feature-point trajectory generation section is provided to generate, based on the first coordinates, a trajectory of the feature point group. A second measuring device measures a location of its own vehicle relative to a feature point located rearward of the feature point measured by the first measuring device. An anomaly determination section is provided to determine that anomaly occurs in a self-location estimation device if the second coordinates are on the trajectory.

Abstract: A vicinity supervising device of a vehicle includes an image capturing unit capturing a plurality of images at different locations; a distance acquiring unit acquiring a distance up to the object detected by transmitting and receiving probing waves from/to the object; a first offset calculation unit calculating a first parallax offset value based on the plurality of images and the distance up to the object; and a second offset calculation unit calculating a second parallax offset value based on a change in a parallax in a predetermined period at an identical point among the plurality of images and a travel distance of the vehicle travelling in a predetermined period; and a parallax correction unit correcting the parallax using the first parallax offset value under a condition where a difference between the first parallax offset value and the second parallax offset value is less than or equal to a threshold.

Abstract: Described is a system for multi-view embedding for object recognition. During operation, the system receives an input image and transforms raw data of objects in the image with corresponding labels into low-level features and high-level semantic representations of the labels. A trained object recognition model is generated by embedding the low-level features with multiple high-level semantic representations. The system then receives data of an unknown object and assigns a label to the unknown object using the trained object recognition model. Finally, a device can be controlled based on the label.

Abstract: Methods and systems for providing fast semantic proposals for image and video annotation including: extracting image planes from an input image; linearizing each of the image planes to generate a one-dimensional array to extract an input feature vector per image pixel for the image planes; abstracting features for a region of interest using a modified echo state network model, wherein a reservoir increases feature dimensions per pixel location to multiple dimensions followed by feature reduction to one dimension per pixel location, wherein the echo state network model includes both spatial and temporal state factors for reservoir nodes associated with each pixel vector, and wherein the echo state network model outputs a probability image; post-processing the probability image to form a segmented binary image mask; and applying the segmented binary image mask to the input image to segment the region of interest and form a semantic proposal image.

Abstract: Embodiments of the present disclosure disclose a lane line identification modeling method and apparatus, and a lane line identification method and apparatus. The lane line identification modeling method includes: identifying an image region of a lane line in an image based on two-dimensional filtering (S11); constructing model training data by using the identified image region (S12); and training a convolutional neural network-based lane line identification model by using the model training data (S13). The lane line identification modeling method and apparatus, and the lane line identification method and apparatus provided in the embodiments of the present disclosure can improve the accuracy of lane line detection.

Abstract: A system mountable in a vehicle to provide object detection in the vicinity of the vehicle. The system includes a camera operatively attached to a processor. The camera is mounted externally at the rear of the vehicle. The field of view of the camera is substantially in the forward direction of travel of the vehicle along the side of the vehicle. Multiple image frames are captured from the camera. Yaw of the vehicle may be input or the yaw may be computed from the image frames. Respective portions of the image frames are selected responsive to the yaw of the vehicle. The image frames are processed to detect thereby an object in the selected portions of the image frames.

Abstract: Aspects of the disclosure relate to generating a grid or a visual list to facilitate operator review of labels. The system receives a first set of labels generated by a first labeling source and a second set of labels generated by a second labeling source. The first set of labels and the second set of labels each classify one or more objects perceived in one or more scenes captured by a sensor of a vehicle, such that each of the one or more objects has a corresponding first label and a corresponding second label. The system determines discrepancies between the corresponding first label and the corresponding second label for each of the one or more objects, and generates a grid or a visual list using the determined discrepancies. The system provides the grid or the visual list for display to a human operator.

Abstract: Aspects described herein may allow for the application of an artificial neural network architecture to identify intrusion in a database. Changes to components of a data table of the database may be tracked as a snapshot of the changes over a period of time. Any change in the data table may be associated with a user. Utilizing multiple snapshots, a background substitution technique may be utilized to generate a matrix of the changes to the data table over a period of time. A model having an artificial neural network architecture may utilize the matrix as an input set to identify the user as an unauthorized user accessing the database.

Abstract: Disclosed is an apparatus and method for processing information of multiple cameras.

Abstract: The disclosure relates to a method and system to operate a motor vehicle with a congestion assistant. The congestion assistant enters sensor data, which serves as input data of the congestion assistant. The sensor data is evaluated, via an evaluation unit, in order to define a value representing a signal roughness of the sensor data. The value is compared, via a comparison unit, with a threshold value. A suppression signal is generated, via a signal detection unit, to prevent automatic activation of the congestion assistant if the value is greater than the threshold value.

Abstract: The invention relates to a method for generating a surroundings map (12) of a surroundings area (8) of a motor vehicle (1), in which method the surroundings area (8) is captured by way of at least one sensor, in particular ultrasound sensor (5, 6, 14, 15), on the motor vehicle, wherein capturing of the surroundings area (8) by way of the at least one sensor (5, 6, 14, 15) is performed at at least two different points in time (T1, T2), and in a manner dependent on said surroundings clearance situations detected in each case in a manner dependent on items of sensor information at the points in time (T1, T2), a decision is made as regards whether an object (11, 13) which is at least supposedly situated in the surroundings area (8) in at least one surroundings clearance situation is, upon an updating of the surroundings map (12), displayed on the then updated surroundings map (12). The invention also relates to a driver assistance system (2) and to a motor vehicle (1).

Abstract: Systems and methods for operating a vehicle are provided. In one example, an apparatus comprises a portion of a window of the vehicle having a configurable light transmittance, an image output device, and a controller configured to operate in a first mode when the vehicle is partially or fully controlled by a driver inside the vehicle and to operate in a second mode when the vehicle is not controlled by a driver inside the vehicle. In the first mode, the controller can adjust a light transmittance of the portion of the window to a first value to enable the driver inside the vehicle to see through the window. In the second mode, the controller can adjust the light transmittance of the portion of the window to a second value lower than the first value, and control the image output device to display an image on the portion of the window.

Abstract: Three-dimensional point group data indicating three-dimensional coordinate sets of three-dimensional points included in a common imaging space of one or more cameras is received, one or more images captured by the one or more cameras are transmitted, the one or more transmitted images are received, initial camera parameters of each cameras are decided based on one or more mounting locations and one or more directions of the cameras, corresponding points in the one or more images are calculated for each of the three-dimensional points, based on the three-dimensional point group data and the initial camera parameters, and one or more camera parameters of the one or more cameras are calculated based on pixel values at the corresponding points in the one or more images.

Abstract: A display control device for a vehicle includes at least one electronic control unit configured to: cause a display device to display a host vehicle's behind-the-vehicle image, the host vehicle's behind-the-vehicle image being an image of an area behind a host vehicle, the host vehicle's behind-the-vehicle image being captured by a sensor of the host vehicle; detect a rearward vehicle, the rearward vehicle being another vehicle existing behind the host vehicle; cause the display device to display the host vehicle's behind-the-vehicle image with a first contrast ratio when the rearward vehicle is not detected; and cause the display device to display the host vehicle's behind-the-vehicle image with a second contrast ratio when the rearward vehicle is detected, the second contrast ratio being higher than the first contrast ratio.

Abstract: Present disclosure provides a travel assistance device which comprises: a road detection unit that obtains an infrared image in front of a vehicle from an infrared imaging unit that is mounted on the vehicle, and detects a road end line of a road on which the vehicle travels from the captured infrared image; a division line detection unit that obtains a visible image in a range corresponding to a range indicated by the infrared image from a visible imaging unit that is mounted on the vehicle, and detects a division line of the road from the captured visible image; an image generation unit that generates an integrated image indicating the road end line and the division line on the basis of the infrared image and the visible image registered with each other; and a division line estimation unit.

Abstract: Systems and methods are disclosed for a pixelated light source that includes a plurality of pixels; a plurality of digital micromirrors configured to receive input light from the pixelated light source and configured to modify the input light to generate output light; and one or more controllers configured to control both the pixelated light source and the plurality of digital micromirrors to condition the output light.

Abstract: Camera pose optimization, which includes determining the position and orientation of a camera in three-dimensional space at different times, is improved by detecting a higher-confidence reference object in the photographs captured by the camera and using the object to increase consistency and accuracy of pose data. Higher-confidence reference objects include objects that are stationary, fixed, easily recognized, and relatively large. In one embodiment, street level photographs of a geographic area are collected by a vehicle with a camera. The captured images are geo-coded using GPS data, which may be inaccurate. The vehicle drives in a loop and captures the same reference object multiple times from the substantially same position. The trajectory of the vehicle is then closed by aligning the points of multiple images where the trajectory crosses itself. This creates an additional constraint on the pose data, which in turn improves the data's consistency and accuracy.

Abstract: The present disclosure provides a driving assist system including: a determiner configured to determine whether a current road is an intersection on the basis of camera information obtained from a stereo camera for monitoring the front area of a vehicle; and an adjuster configured to adjust the direction of a first field of view (FOV) or a second field of view such that the overlap area of the first field of view and the second field of view that are the fields of view of a first camera and a second camera included in the stereo camera is reduced, when the current road is determined as an intersection.

Abstract: A method for dynamically ascertaining alignment of a vehicular camera relative to a vehicle to which the camera is attached includes determining a plurality of steering angle ranges for the vehicle, each of which is a range of steering angles that approximates straight vehicle motion over less than two seconds of travel time of the vehicle while the vehicle is in motion and turning. Image data captured by a camera of the vehicle is processed to determine a central vanishing point when the vehicle is in motion and moving straight. A plurality of feature points are selected in the image frames for each steering angle range, and a vanishing point for a plurality of tracked motion trajectories for each steering angle range is determined. An alignment of the camera is determined based at least in part on the determined central vanishing point and a determined vanishing line.

Abstract: A parking position identification method includes acquiring input data as an image that is generated by photographing a parking region by a camera which is installed in a target vehicle, and identifying a parking position of the target vehicle in the photographed parking region by inputting the input data to a learning model that indicates a relationship between the parking region which has a width in which parking of at least one vehicle is feasible and a parking position for one vehicle in the parking region.

Abstract: A distance measurement device includes a deriving unit that derives a dimension of a real-space region corresponding to an interval between a plurality of pixels associated with in-image irradiation positions derived as positions, which correspond to irradiation positions of laser beams onto a subject, within a captured image acquired by imaging the subject by an imaging unit, based on a distance measured by a measurement unit, an interval between a plurality of designated pixels, and a focal length of the imaging unit, and an output unit that derives derivation accuracy corresponding to an actually present factor based on a first correspondence relation between assumption factors assumed as factors influencing in-image irradiation positions and derivation accuracy derived by the deriving unit, and outputs information based on the derived derivation accuracy.

Abstract: Systems and methods are disclosed for tire management that can detect various aspects of tires and determine tire status, from tires rotating on a moving vehicle.

Abstract: A vehicle lateral control system having a lane model with modulation weighting for controlling a vehicle includes a camera, an image processing device, a controller and a steering device. The camera is configured to capture a front image of the vehicle to generate a front image dataset. The front image dataset is analyzed by the image processing device to obtain a plurality of lane markers, and the image processing device establishes a lane fitting curve according to the lane markers and a target weighting. The controller has a plurality of vehicle dynamic parameters and a target distance. The target weighting is changeable according to the target distance. The controller generates a steering control weighting according to the lane fitting curve and the vehicle dynamic parameters. The steering device is configured to control a turning direction of the vehicle according to the steering control weighting.

Abstract: A windshield assembly is provided herein. The windshield assembly includes a windshield having a frit and an indicator thermally coupled to the windshield to visually coincide with the frit and operable to illuminate in order to indicate a relative temperature of the windshield.

Abstract: A fast lane driving warning unit and a method are disclosed, in which images in front of a vehicle (6) which runs on a road that comprises a fast lane (L1) are continuously captured, the images to determine whether the vehicle (6) is driving in the fast lane (L1) are analyzed; and a warning signal is sent out when the following conditions are both met: the vehicle (6) runs in the fast lane (L1) at a vehicle speed lower than a lower limit of an allowed speed range of the fast lane (L1) over time longer than a preset time period; and the current traffic condition of the fast lane (L1) permits the vehicle (6) to run in the allowed speed range of the fast lane (L1).

Abstract: Apparatus and methods are described for roadway lane line detection. An aerial image including a plurality of pixels is received and provides to a classification model. The classification model provides probability values assigned to at least a portion of the plurality of pixels. A comparison of the probability values is performed to select at least one pixel according to the comparison. A lane line object is identified for the selected at least one pixel.

Abstract: An automatic driving system for an automatically driven vehicle. In the system, a travel direction acquirer is configured to acquire travel direction information that is information indicative of whether or not each of lanes in a parking lot is unidirectional. In addition, in the system, an allowance determination unit is configured to, if determining, based on the travel direction information acquired by the travel direction acquirer, that each of the lanes in the parking lot is unidirectional, allow automatic driving of the automatically driven vehicle.

Abstract: A method in a lidar system for scanning a field of regard of the lidar system is provided. The method includes identifying, within the field of regard, a ground portion that overlaps a region of ground located ahead of the lidar system; causing a light source to emit pulses of light; scanning at least a portion of the emitted pulses of light along a scan pattern contained within the field of regard, including adjusting a scan parameter so that at least one of a resolution or a pulse energy for the ground portion of the field of regard is modified relative to another portion of the field of regard; and detecting at least a portion of the scanned pulses of light scattered by one or more remote targets.

Abstract: A computing device receives an image and a video segment of a road scene, the first at least one of an image and a video segment being taken from a perspective of a participant in the road scene and then generates stimulus data based on the image and the video segment. Stimulus data is transmitted to a user interface and response data is received, which includes at least one of an action and a likelihood of the action corresponding to another participant in the road scene. The computing device aggregates a subset of the plurality of response data to form statistical data and a model is created based on the statistical data. The model is applied to another image or video segment and a prediction of user behavior in the another image or video segment is generated.

Abstract: In one embodiment, a system of detecting seat belt operation in a vehicle includes at least one light source configured to emit a predetermined wavelength of light onto structures within the vehicle, wherein at least one of the structures is a passenger seat belt assembly having a pattern that reflects the predetermined wavelength at a preferred luminance. At least one 3-D time of flight camera is positioned in the vehicle to receive reflected light from the structures in the vehicle and provide images of the structures that distinguish the preferred luminance of the pattern from other structures in the vehicle. A computer processor connected to computer memory and the camera includes computer readable instructions causing the processor to reconstruct 3-D information in regard to respective images of the structures and calculate a depth measurement of the distance of the reflective pattern on the passenger seat belt assembly from the camera.

Abstract: A computer implemented method of event based video generation, comprising: on the device, receiving a feed of video captured by a camera, on a memory of the device, maintaining at least one buffer storing a most recent portion of the video feed being received, on a display of the device, presenting at least one GUI element, each one of the GUI elements being associated with a respective predefined video length, and upon actuation of one of the GUI elements by a user of the device, forwarding at least a sub-portion of the video feed portion stored in the buffer for further processing, the forwarded sub-portion having the predefined video length associated with the GUI element actuated by the user.

Abstract: A door arrangement (1), includes a safety device. A door arrangement monitoring method monitors a monitored area positioned in front of a door opening, offset and parallel to a door closing plane, and performs a failure routine when an object (6) is detected in the monitored area and there is a risk of a collision of the object (6) with a door leaf (2). A current position of the object (6), and of a leading edge (23) of the door leaf (2), are detected. A direction of movement of the door leaf (2) is detected. The failure routine is initiated as a function of the current position of the object (6) and the leading edge (23) of the door leaf (2) as well as the direction of movement of the door leaf (2).

Abstract: An apparatus comprising an interface and a processing circuit. The interface may be configured to receive (a) a video signal based on a targeted view in a vehicle and (b) one or more status signals from one or more sensors of the vehicle. The processing circuit may be configured to (A) analyze the video signal received from the interface and (B) detect a type of obstruction of a window of the vehicle visible in the video signal in response to (i) a classification of information in the video signal and (ii) one or more of the status signals. The processing circuit may (a) determine a confidence level for the type of obstruction, (b) activate one or more corrective measures when the confidence level is above a pre-defined threshold and (c) adjust the confidence level based on a response of the obstruction to the corrective measures.

Abstract: The invention relates to audio signal processing apparatuses and methods, such as an audio signal downmixing apparatus (105) for processing an input audio signal comprising a plurality of input channels (113) into an output audio signal comprising a plurality of primary output channels (123) and at least one auxiliary output channel (125) using a downmix matrix D, wherein the downmix matrix D comprises a primary downmix matrix DU providing the plurality of primary output channels (123) and an auxiliary downmix matrix DW providing the at least one auxiliary output channel (125). The audio signal downmixing apparatus (105) comprises an auxiliary downmix matrix determiner (107) configured to determine the auxiliary downmix matrix DW, and a processor (109) configured to process the input audio signal into the output audio signal using the downmix matrix D.

Abstract: Systems and method are provided for localizing a vehicle. In one embodiment, a method includes: receiving, by a processor, sensor data from a sensor of the vehicle; filtering, by the processor, the sensor data for data associated with static elements of the environment; determining, by the processor, realtime height values associated with the static elements; correlating, by the processor, the realtime height values with defined height values associated with a map of the environment; localizing, by the processor, the vehicle on the map based on the correlated realtime height values and the defined height values; and controlling, by the processor, the vehicle based on the localizing.

Abstract: A vehicle system, comprising a vehicle transceiver located in the host vehicle configured to receive data indicative of a driving path of one or more remote vehicles, a processor in communication with the vehicle transceiver and programmed to output graphical images indicative of lane markers on a road to the display utilizing at least the driving path data, and a display configured to display the graphical images.

Abstract: An automatic travel vehicle includes a body, a drive unit to move the body on a travel surface along a travel guide line, a detection unit to detect a mark attached to one adjacent portion of the travel guide line for one spot set along the travel guide line, and a control unit to control an operation of the automatic travel vehicle based on the detected mark. The control unit interprets the mark attached to the one adjacent portion of the travel guide line at a first side of the body when the automatic travel vehicle travels along the travel guide line in a first travelling direction, and interprets the mark attached to the one adjacent portion of the travel guide line at a second side of the body when the automatic travel vehicle travels along the travel guide line in a second travelling direction.

Abstract: A method is provided for use in a stereoscopic image generating system, the system including at least two image capturing sensors and at least one aggregation processor. The at least one aggregation processor is configured to: receive data associated with an image captured by the image capturing sensors; calculate aggregation results for a pre-defined number of disparity levels based on data received from one of the at least two image capturing sensors; estimate aggregation results for data received from another image capturing sensor; and combine the calculated results with the estimated results.

Abstract: A method of lane change and path planning that receives sensed signals from multiple sensors through a car computer on a vehicle to generate multiple traveling speed time-sorted information and multiple surrounding circumstance time-sorted information, and to further generate a 3×3 grid corresponding to the surroundings of the vehicle; when receiving a signal to switch on the turn signals, the car computer selects data within a time interval from those traveling speed time-sorted information and surrounding circumstance time-sorted information, respectively; and then the selected data is to be processed together with the 3×3 grid to generate a lane change space, and through a decision strategy to determine whether the lane change space complies with a safety movement strategy, and then the car computer generates a planned path of movement, such that a safest space for assisting lane change is provided for improving convenience and safety.

Abstract: A method includes receiving a first set of images from an image capture device of a vehicle. The method also includes performing a first analysis of movement of biomechanical points of occupants of the vehicle in the first set of images. The method further includes receiving an indication that a traffic incident has occurred. The method also includes receiving a second set of images from the image capture device corresponding to when the traffic incident occurred. The method further includes performing a second analysis of movement of the biomechanical points of the occupants in the second set of images. The method also includes determining a likelihood of injury or a severity of injury to the occupants based on the first analysis of movement and the second analysis of movement.

Abstract: A repetitive structure extraction device includes an image feature extraction unit which extracts an image feature for each of a plurality of images which are captured at one or a plurality of locations and which are given different capture times, a temporal feature extraction unit which extracts, for each of the plurality of images, a temporal feature according to a predetermined period from a capture time given to the image, and a repetitive structure extraction unit which learns, on the basis of the image feature extracted for each of the plurality of images by the image feature extraction unit and the temporal feature extracted for each of the plurality of images by the temporal feature extraction unit, a repetitive structure which is used to perform interconversion between the temporal feature and a component of the image feature and which is provided according to a correlation of periodic change between the component of the image feature and the temporal feature.

Abstract: An artificial intelligence (AI) system for simulating functions such as recognition, determination, and so forth of human brains by using a mechanical learning algorithm like deep learning, or the like, and an application thereof is provided. A method of providing a text-related image is provided. The method includes obtaining a text, determining at least one image related to the obtained text based on a degree of relatedness between a result of applying a first AI data recognition model to the obtained text and a result of applying a second AI data recognition model to a user-accessible image, and displaying the determined at least one image to a user.

Abstract: The disclosure discloses a method for detecting a vehicle in a driving assisting system. The method for detecting a vehicle in a driving assisting system includes: obtaining an image to be detected, and determining the positions of lane lines in the image to be detected; determining a valid area in the image to be detected, according to the positions of the lane lines, and the velocity of the present vehicle; and determining a detected vehicle in the valid area according to T preset weak classifiers, and thresholds corresponding to the respective weak classifiers, wherein T is a positive integer.

Abstract: A control system fuses different sensor data together to determine an orientation of a vehicle. The control system receives visual heading data for the vehicle from a camera system, global navigation satellite system (GNSS) heading data from a GNSS system, and inertial measurement unit (IMU) heading data from an IMU. The control system may assign weights to the visual, GNSS, and IMU heading data based on operating conditions of the vehicle that can vary accuracy associated with the different visual, GNSS, and IMU data. The control system then uses the weighted visual, GNSS, and IMU data to determine a more accurate vehicle heading.