A display method for a display assembly, a display system, and a display device of a vehicle column A, and a storage medium. According to the display method, by means of a conversion relationship between a coordinate system of a target feature model and a camera coordinate system of a driver monitoring assembly and a conversion relationship between the coordinate system of the target feature model and a world coordinate system, a conversion relationship between the camera coordinate system and the world coordinate system is obtained, a coordinate of the display assembly in the world coordinate system can be converted into a coordinate in the camera coordinate system, and thus whether a driver watches the display assembly can be simply determined. The problem that it is difficult to determine, directly according to the eyes of the driver and a spatial position of the display assembly, whether the driver watches the display assembly is solved, and the effect of reducing the difficulty of determining whether the driver watches the display assembly is achieved.

The present invention provides a processing apparatus (10) including an acquisition unit (11) that acquires a capture image capturing a movement means, an image analysis unit (12) that computes, based on the capture image, the number of persons each having an attribute satisfying a first criterion among persons inside the movement means, and the number of persons targeted for comparison, a computation unit (13) that computes a ratio of the number of persons satisfying the first criterion to the number of persons targeted for comparison, and an output unit (14) that outputs alert information when the ratio satisfies an alert condition.

A monitoring system includes a first image analysis apparatus provided at an edge of an information communication network together with a camera, and configured to analyze a captured image of a monitored space imaged by the camera so as to execute detection and determination of a state change occurring in the monitored space, an image distribution apparatus configured to execute distribution of the captured image via the information communication network when occurrence of the state change is detected, and a second image analysis apparatus configured to analyze the distributed captured image so as to execute detection and determination of an abnormality occurring in the monitored space.

A first 2D recording of a specified reference view of an object is captured by a camera and, starting from the first 2D recording, a user's starting location relative to the object is ascertained by a computer vision module. Starting from the origin of a coordinate system as the starting location of the camera, one or more specified and/or settable relative positions in the vicinity of the object and/or in the object are determined as one or more locations for the respective perspective of the camera for taking at least one second 2D recording. The respective location in an object view on a display of the camera is displayed by a respective first augmented reality marker on the ground and/or on the object. The alignment of the camera with regard to angle and rotation with the perspective corresponding to the respective location is performed in this case by second augmented reality markers as auxiliary elements.

A system and method for detecting seatbelt positioning includes capturing, by a camera, a near infrared (NIR) image of an occupant, applying a median filter to the NIR image to remove glints; converting the NIR image to a black-and-white image, scanning across the black-and-white (B/W) image to detect a plurality of transitions between black and white segments corresponding to stripes extending lengthwise along a length of the seatbelt, and using detections of the plurality of transitions to indicate a detection of the seatbelt. Converting the NIR image to the black-and-white image may include using a localized binary threshold to determine whether a given pixel in the B/W image should be black or white based on whether a corresponding source pixel within the NIR image is brighter than an average of nearby pixels within a predetermined distance of the corresponding source pixel.

According to the techniques of this disclosure, a method includes capturing, using a camera system of a vehicle, at least one image of an occupant of the vehicle, determining, based on the at least one image of the occupant, a location of one or more eyes of the occupant within the vehicle, and determining, based on the at least one image of the occupant, an eye gaze vector. The method may also include determining, based on the eye gaze vector, the location of the one or more eyes of the occupant, and a vehicle data file of the vehicle, a region of interest from a plurality of regions of interests of the vehicle at which the occupant is looking, wherein the vehicle data file specifies respective locations of each of the plurality of regions of interest, and selectively performing, based on the region of interest, an action.

Devices, methods, and processor-readable media for eye tracking using statistically derived linear functions are described. Two simple linear functions may be identified, one for the horizontal and one for the vertical, with two parameters each, that fully correct for horizontal and vertical estimation bias error in a cross-ratio gaze estimation method. An implicit calibration step may be performed that finds the parameters of said linear functions statistically based on undirected user point of gaze measurements that indicate the extremities of the error between gaze vectors and glint vectors. Various hardware devices are described that may implement the novel eye tracking techniques.

An automated charging system for an electric vehicle is disclosed that includes a plug with a built-in camera assembly. The camera assembly captures images of a charging port of the electric vehicle, which are processed by one or more processors to estimate the location of the charging port relative to the plug. A control system generates signals for one or more actuators to move the plug relative to the charging port, thereby inserting the plug into the charging port to connect a power supply to the electric vehicle. The images may be processed via an image recognition algorithm and/or one or more machine learning algorithms. In an embodiment, the images are processed by a neural network to estimate the location of the charging port relative to the plug. The plug can also include a tapered structure to make fine adjustments to the position or orientation of the plug during connection.

A vehicle characterizes a sunload on the vehicle using an imaging system including at least one camera capturing image data (e.g., without using an ambient light sensor). The image data includes at least a portion of a passenger cabin. A region of interest (ROI) overlay receives the image data and extracts selected image data according to predetermined scene elements of the vehicle environment. An occupant overlay is configured to detect a vehicle occupant represented in the selected image data and configured to generate truncated image data by subtracting image data corresponding to the vehicle occupant from the selected image data. An ambient light model uses environmental parameters including a sun position to estimate an expected sunload range. A mapper generates a sunload map comprising respective sunload values for a plurality of locations on the vehicle according to the truncated image data and the expected sunload range.

A machine-implemented method for automated detection of drowsiness, which includes receiving from an imaging device directed at the face of an operator a series of images of the face of the operator onto processing hardware, on the processor detecting facial landmarks of the operator from the series of images to determine the level of talking by the operator, the level of yawning of the operator, the PERCLOS of the operator, on the processor detecting the facial pose of the operator from the series of images to determine the level of gaze fixation by the operator, on the processor calculating the level of drowsiness of the operator by ensembling the level of talking by the operator, the level of yawning of the operator, the PERCLOS of the operator and the level of gaze fixation by the operator, and generating an alarm when the calculated level of drowsiness of the operator exceeds a predefined value.