In a method of producing images of a stored three-dimensional model of the surroundings of a vehicle, the images are corrected for perspective. A camera picture is produced by a camera device of the vehicle, and is projected onto a projection surface in the surroundings model. A region relevant for driving is marked in the surroundings model and is projected onto a corresponding projection surface area of the projection surface. An image of the projection surface including the driving-relevant region projected onto the projection surface area is produced and output by a virtual camera that can move freely in the surroundings model.

Provided is an on-vehicle processing device that can estimate the position of a vehicle with higher accuracy. A storage unit stores a parking lot point group including a plurality of coordinates of points of a part of an object in a parking lot coordinate system. A sensor input unit acquires peripheral information from a camera. A movement information acquisition unit acquires movement information. A local peripheral information creation unit generates local peripheral information expressing second point group data including a position of the vehicle in a local coordinate system and a plurality of coordinates of points of a part of the object in the local coordinate system on the basis of the peripheral information and the movement information. A position estimation unit estimates a correlation between the parking lot coordinate system and the local coordinate system on the basis of the parking lot point group and the local peripheral information, and estimates the position of the vehicle in the parking lot coordinate system from the position of the vehicle in the local coordinate system and the correlation.

An image processing device includes: a setting unit configured to set an area, as a first area, in which at least one delimiting line for delimiting a parking space is detected in a first image of plural images continuously captured while moving; and a prediction unit configured to predict, based on the first area, a second area in which the at least one delimiting line is to be detected in at least one second image of the plural images, the at least one second image being captured later in time than the first image.

Tracking the use of at least one destination location is disclosed. Initially, one or more first images of a parking display ticket within a vehicle that is occupying a destination location are received from a first camera of an unmanned air vehicle that is configured to be autonomously operated. Parking information for the vehicle occupying the destination location is determined based on at least one of the one or more first images of the parking display ticket. A unique identifier of the vehicle occupying the destination location is also determined. The parking information for and the unique identifier of the vehicle occupying the destination location is then indicated.

A vehicle control system for moving a vehicle to a target location is disclosed. According to examples of the disclosure, a camera captures one or more images of a known object corresponding to the target location. An on-board computer having stored thereon information about the known object can process the one or more images to determine vehicle location with respect to the known object. The system can use the vehicle's determined location and a feedback controller to move the vehicle to the target location.

A display control device includes a video data acquiring unit that acquires video data from a plurality of cameras photographing a periphery of a vehicle, a bird's-eye view video generator that applies view point conversion processing and synthesis processing to the video data to generate a bird's-eye view video, an adjacent information acquiring unit that acquires first obstacle information serving as information about obstacles around the vehicle when the vehicle has moved backward and entered the parked state, and second obstacle information serving as the information about the obstacles around the vehicle when the vehicle moves forward to exit the parked state, a comparing unit that compares the first obstacle information with the second obstacle information to determine whether the number of obstacles around the vehicle has increased when the vehicle exits the parked state, and a display controller.

A vehicular vision system includes a plurality of cameras and a processor operable to process image data captured by the cameras to generate images derived from image data captured by at least some of the cameras. A display screen, viewable by a driver of the vehicle, displays the generated images and a three dimensional vehicle representation as would be viewed from a virtual camera viewpoint exterior to and higher than the vehicle itself. A portion of the displayed vehicle representation may be at least partially transparent to enable viewing at the display screen of an object present exterior of the vehicle that would otherwise be partially hidden by non-transparent display of that portion of the vehicle representation. The three dimensional representation may include a vector model without solid surfaces, or may include a shape, body type, body style and/or color corresponding to that of the actual vehicle.

Methods and systems for digital image segmentation and annotation, including: receiving a digital image depicting, in part, an object of interest from an input file; one or more of manually and automatically adding a polygon around the object of interest to generate a segmented digital image; one or more of manually and automatically appending a label to the polygon around the object of interest to generate a segmented and annotated digital image, wherein the label indicates one or more of an identity and a characteristic of the object of interest; and outputting information related to the segmented and annotated digital image to an output file. Optionally, the polygon is one of a bounding box and a 4-point polygon. Optionally, the object of interest is a parking spot.

An image processor includes a parking area line detection portion configured to detect a parking area line from an image acquired by an imaging device, a parking frame setting portion configured to set a parking frame based on the detected parking area line, a parking frame selection portion configured to calculate a length ratio of adjacent first and second sides of the set parking frame, determine the parking frame as a display target when the length ratio falls within a predetermined range, and not to determine the parking frame as the display target when the length ratio falls outside the predetermined range, and a display control portion configured to control a display portion for displaying a parking frame image showing the parking frame determined as the display target by the parking frame selection portion so as to keep superimposing the parking frame image onto the image.

The present application discloses a method and a device for controlling a vehicle, and a vehicle and relates to the field of automatic driving and deep learning technology. The specific implementation solution is: acquiring a current image of a road section in front of the vehicle, and acquiring a parking trajectory path of the vehicle; acquiring a deep convolutional neural network model corresponding to the parking trajectory path; inputting the current image to the deep convolutional neural network model to acquire slope information of a road section in front of the vehicle; determining longitudinal acceleration of the vehicle according to the slope information; and controlling the vehicle according to the longitudinal acceleration.