Techniques including receiving a distorted image from a camera disposed about a vehicle, detecting, in the distorted image, corner points associated with a target object, mapping the corner points to a distortion corrected domain based on one or more camera parameters, mapping the corner points and lines between the corner points back to a distorted domain based on the camera parameters, interpolating one or more intermediate points to generate lines between the corner points in the distortion corrected domain mapping the corner points and the lines between the corner points back to a distorted domain based on the camera parameters, and adjusting a direction of travel of the vehicle based on the located target object.

A control device for vehicle is provided, and includes a communicator configured to receive first image information from a camera device and a processor coupled to the communicator and configured to: extract label information in the first image information; perform edge detection on the label information and extract a total number of edges; normalize the total number of edges to form a first label clarity; and when the first label clarity is greater than or equal to a preset threshold, control the vehicle to move to a parking position according to the first image information. A control method for vehicle is also provided. The present disclosure can effectively reduce the number of starts and stops of the vehicle and shorten the parking time of the vehicle.

A method for vehicle parking detection, a system for vehicle parking detection, an electronic device and a storage medium are disclosed. The method includes: obtaining a first lateral distance between a vehicle and a reference object in a site by a first distance sensor; obtaining a second lateral distance between the vehicle and the reference object by a second distance sensor; collecting a first scene image by a first camera, and obtaining a first longitudinal distance based on the first scene image, the first longitudinal distance being a distance between a first mark line on the vehicle and a first parking line in the site; and determining whether the vehicle is parked at a target location in the site based on the first lateral distance, the second lateral distance and the first longitudinal distance.

The present disclosure provides various approaches for smart area monitoring suitable for parking garages or other areas. These approaches may include ROI-based occupancy detection to determine whether particular parking spots are occupied by leveraging image data from image sensors, such as cameras. These approaches may also include multi-sensor object tracking using multiple sensors that are distributed across an area that leverage both image data and spatial information regarding the area, to provide precise object tracking across the sensors. Further approaches relate to various architectures and configurations for smart area monitoring systems, as well as visualization and processing techniques. For example, as opposed to presenting video of an area captured by cameras, 3D renderings may be generated and played from metadata extracted from sensors around the area.

A vehicular vision system includes a plurality of cameras and a processor operable to process image data captured by the cameras. The plurality of cameras includes a front camera, a rear camera, a driver-side camera and a passenger-side camera. Images derived from image data captured by at least some of the cameras are displayed on a display screen of the vehicle for viewing by a driver of the vehicle during a driving maneuver of the vehicle. During the driving maneuver of the vehicle, the display screen displays a three dimensional vehicle representation as would be viewed from a viewpoint exterior to the vehicle. A portion of the displayed three dimensional vehicle representation is at least partially transparent. A degree of transparency of the portion of the displayed three dimensional vehicle representation is adjustable

A position estimation apparatus includes: an image information calculation unit that extracts each of image feature points from a plurality of images which are sequentially captured and associates the image feature points with each other between the plurality of images; a travel amount calculation unit that estimates the position of the mobile object; a three-dimensional image feature point calculation unit that estimates a three-dimensional position of the image feature point in a real space on the basis of a result of associating the image feature points with each other and the position of the mobile object; a position correction unit that corrects the three-dimensional position and the position of the mobile object so as to reduce a position error between a position of the three-dimensional position, when the three-dimensional position is reprojected onto any one of the plurality of images, in the relevant image and the image feature point; a route regeneration judgment unit that judges whether or not to regenerate the route on the basis of a result of comparison between the corrected position of the mobile object and the route.

A method of aligning a tow vehicle with a trailer positioned behind the tow vehicle is provided. The method includes determining a point cloud map of a rear environment of the tow vehicle. The rear environment includes the trailer. The method also includes determining a front face plane of the trailer based on the point cloud map. The method also includes determining a normal line of the front face plane. The method also includes determining a path from the tow vehicle to the trailer such that a fore-aft axis of the tow vehicle is aligned with the normal line of the front face plane.

A system of estimating ambient light includes an image sensor that captures an image; a region of interest (ROI) selector that determines at least one ROI on the image; an occupancy detector that determines existence status of an object disposed on the at least one ROI; and an ambient light estimator that estimates illumination of ambient light of the at least one ROI according to luminance of the at least one ROI on the image.

A method for securing a starting movement of a semi-automated or fully automated vehicle, the vehicle including at least one imaging sensor, which is configured to capture images of a close-up range of the vehicle. A recognition of objects in the close-up range of the vehicle is carried out. A starting movement of the vehicle is prevented if an object has been recognized.

The present disclosure relates to a method for generating a view for a camera system, in particular a surround-view camera system for a vehicle, including a control device and at least one camera, wherein the view is generated by means of the following method steps: capturing at least one object from the environment data from the at least one camera; generating a bounding box for the object; projecting the object onto a ground plane; creating a bounding shape which includes the bounding box and the projected object; creating a mesh structure or grid structure for the bounding shape; and arranging the mesh structure or grid structure within the bounding box, wherein the bounding shape is adapted, in particular by image scaling and/or image distortion, to the size of the bounding box.