A method for processing images is described, wherein a scenery is recorded as at least one raw image by at least one optical capture means mounted on a vehicle, and wherein image data of the scenery are mapped incompletely and/or erroneously in the subsequently rendered render image in at least one area. In order to provide a user of one or more cameras on a motor vehicle, that have visibility restrictions with a more agreeable visual experience, the method includes identifying the area(s) of incomplete and/or erroneous mapping in the render image on the basis of existing visibility restrictions, generating masks that enclose the area(s) of incomplete and/or erroneous mapping as masked areas, reconstructing image data in unmasked areas of the render image by means of digital inpainting and synthesizing together with the masked areas to produce a correction image, and displaying the completed and/or debugged correction image.

A method and system for autonomous parking are disclosed. The system employs Homography guided motion segmentation (HGMS) to determine the availability of a parking slot. A free parking slot is determined based on an occupancy status check and identified structures of parking lines. For example, motion analysis is performed on successive images captured by a camera unit to determine the occupancy status of a parking slot. Information of the free parking slot, for example, the dimensions and orientation, may be determined from identifying the structure of parking lines. This information is used by the system to guide a vehicle from its current location to the detected free parking slot.

A method of tracking a mobile device comprising at least one camera in a real environment comprises the steps of receiving image information associated with at least one image captured by the at least one camera, generating a first geometrical model of at least part of the real environment based on environmental data or mobile system state data acquired in an acquisition process by at least one sensor of a mobile system, which is different from the mobile device, and performing a tracking process based on the image information associated with the at least one image and at least partially according to the first geometrical model, wherein the tracking process determines at least one parameter of a pose of the mobile device relative to the real environment. The invention is also related to a method of generating a geometrical model of at least part of a real environment using image information from at least one camera of a mobile device.

Provided is a method and system that includes an imaging device to be disposed in a lighting fixture to capture images, a remote computing device in communication with the imaging device, and comprising at least one processor. The processor is capable of processing data related to images from the at least one imaging device and from a satellite imagery system, performing comparison operation by detecting a first set of points of interest in an image from the at least one imaging device and corresponding second set of points of interest in an image of a same area from the satellite imagery system, and calculating a homography matrix by matching the first set of points of interests in the image from the at least one imaging device and the second set of points of interest in the image from the satellite imagery system, to determine latitude and longitude coordinates of the image from the imaging device.

A system comprising a computer-readable storage medium storing at least one program and a method for determining vehicle overlap with a parking space is presented. The method may include accessing a set of pixel coordinates defining a location of a vehicle within an image, and translating the set of pixel coordinates to a set of global coordinates defining a geospatial location of the vehicle. The method may further include accessing a set of known coordinates of the parking space. The method may further include determining an overlap amount by comparing the global coordinates of the vehicle with the known global coordinates of the parking space, and determining the vehicle overlaps the parking space based on the overlap amount transgressing a threshold overlap amount. The method may further include updating a data object associated with the vehicle to indicate the vehicle overlaps the parking space.

An embodiment LiDAR free space data generator includes a point filter module configured to select input points in a region of interest of an autonomous parking system from a three-dimensional (3D) point cloud obtained from a LiDAR, a two-dimensional (2D) grid map generation module configured to perform 2D grid-wise point processing on the selected input points to generate a first occupied grid feature map, and a multi-modal noise filter module configured to perform grid-level noise filtering, grid-level downsampling, or point-level noise filtering on the first occupied grid feature map to generate first LiDAR free space data.

A method for automatically parking a vehicle in a parking slot involves manually driving the vehicle into the parking slot in a training step, and thereafter automatically driving the vehicle into the parking slot in a replay step. Automatically driving the vehicle into the parking slot involves detecting information of features of the environment of the vehicle corresponding to the driven trajectory, matching feature descriptors of the detected features of the environment with feature descriptors stored in the digital map, and re-localizing the vehicle against the trajectory stored in the digital map in order to navigate the vehicle along the stored trajectory into the parking slot. Automatically driving the vehicle into the parking slot is repeated multiple times, and involves deleting a feature descriptor stored in the digital map if the number of matches does not exceed a threshold after a predefined number of repetitions.

A vehicle parking assist apparatus acquires a camera image when the vehicle stops by a non-determined parking lot and acquires feature points of a ground of an entrance of the non-determined parking lot as non-compared entrance feature points from the camera image. The vehicle parking assist apparatus determines whether the non-determined parking lot is a registered parking lot by comparing information on the non-compared entrance feature points with registered entrance feature point information. The vehicle parking assist apparatus executes a parking assist control with using the currently-acquired parking lot information and the registered parking lot information when the vehicle parking assist apparatus determines that the non-determined parking lot is the registered parking lot.

An image processor includes an edge detection portion for scanning an image and detecting, as edges, an arrangement of pixels in which brightness value difference or color parameter difference between the pixels is equal to or greater than a threshold; a grouping portion for grouping the detected edge based on edge length, a distance between endpoints of the edges, and an angle between the edges; a determination portion for determining the grouped edges as a dashed line edge group when a pattern, in which the brightness value difference or the color parameter difference between the pixels is detected, matches a predetermined pattern; a correction portion for performing a linear approximation process on the dashed line edge group to correct a coordinate value of an endpoint of the dashed line edge; and a parking frame setting portion for setting a parking frame using the corrected dashed line edge.

The present disclosure provides a control method, a vehicle, and a storage medium, wherein the control method comprises: determining lane line information according to image information or map information; determining a parking trajectory according to the lane line information; and controlling the vehicle according to the parking trajectory. In the method, the problem that the vehicle, when the autonomous driving system fails, cannot be safely parked is solved; the image information or the map information is taken as auxiliary information for safe parking, lane line information of a road where the vehicle is located is determined according to the image information or the map information, and assisted parking is performed through the lane line information. The parking trajectory is determined through the lane line information, the vehicle is controlled according to the parking trajectory, and the safe parking of the vehicle is achieved.