A system for calibrating includes an input interface and a calibration parameter determiner. The input interface is configured to receive an image data of a calibrator in front of a camera unit. The camera unit is mounted inside a vehicle. The calibrator is mounted outside the vehicle. The calibration parameter determiner is configured to determine a calibration parameter based at least in part on the image data. The calibration parameter enables determination of an object proximity and a lane pattern.

Disclosed herein are an around view provision apparatus and a vehicle including the same. The around view provision apparatus includes a plurality of cameras mounted on a vehicle, a display, and a processor configured to receive a plurality of images from the plurality of cameras, to check locations of the images using first area patterns in the plurality of images, to compensate a parameter in an image using second area patterns located in overlapping areas between the plurality of images, and to generate an around view image based on the compensated parameter. Accordingly, it is possible to provide an accurate around view image based on a calibrated image.

A method for estimating camera orientation relative to a ground surface. Line segments are detected from an image captured by a camera. A first virtual cube having three orthogonal vanishing points with a random 3D orientation is superimposed on to the image. The line segments of the image are classified grouped into 3D-directional groups. A second virtual cube is superimposed on to the image with an initial 3D orientation. An optimal 3D orientation of the second virtual cube is computed by iteratively changing the 3D orientation of the second virtual cube and measuring perpendicular distances of the three orthogonal vanishing points to the three line segment groups in each iteration starting with the initial 3D orientation, wherein the optimal 3D orientation of the second virtual cube being one that provides shortest perpendicular distances. Co-variances of the orthogonal vanishing points of the second virtual cube at the optimal orientation are computed. Ground orientation is computed from the second virtual cube at the optimal orientation.

A vehicular camera calibration system includes a camera disposed at a vehicle and having a field of view exterior of the vehicle and being operable to capture image data. Responsive to processing of image data captured by the camera, the camera calibration system determines features at the ground adjacent to the vehicle and tracks the determined features over two or more frames of captured image data. Responsive to processing of frames of captured image data during movement of the vehicle along a straight path on a planar surface, the camera calibration system is operable to determine a misalignment of the camera. The camera calibration system calibrates the misaligned camera by using an assumption that the determined features lie in a plane parallel to the planar surface along which the vehicle is traveling. The camera calibration system calibrates the camera by reducing ambiguity in vectors normal to the planar surface.

Disclosed is a display apparatus which considers the speed and traveling mode of a vehicle. The display apparatus includes an information obtaining unit configured to obtain at least one of internal and external information about a vehicle, a control unit configured to process the information obtained by the information obtaining unit into a single image or a plurality of images by using a single image generator and control the image to be changed according to a traveling mode of the vehicle, and a display unit configured to display the image or the plurality of images.

A vision system of a vehicle includes a plurality of cameras with exterior overlapping fields of view. The vision system is operable to calibrate at least one of the cameras and includes a plurality of targets disposed at locations near the vehicle and within the fields of views of the cameras. A display device is operable to display images captured by the cameras of the vision system. A plurality of user inputs may be provided and a user may selectively actuate the user inputs to manipulate images captured by the cameras to align portions of a target in overlapping regions of the captured images of adjacent cameras to calibrate the cameras. The vision system may calibrate cameras automatically, such as responsive to the targets moving into the fields of views of the cameras, whereby the vision system may calibrate the cameras as the vehicle is moved along an assembly line.

A vehicle camera calibration apparatus and method are provided. The vehicle camera calibration apparatus includes a camera module configured to acquire an image representing a road from a plurality of cameras installed in a vehicle, an input/output module configured to receive, as an input, the acquired image from the camera module, or output a corrected image, a lane detection module configured to detect a lane and extract a feature point of the lane from an image received from the input/output module, and a camera correction module configured to estimate a new external parameter using a lane equation and a lane width based on initial camera information and external parameter information in the image received from the input/output module, and to correct the image.

A vehicle periphery monitoring device includes a plurality of sensors including a rear camera, a rear right-side camera, and a rear left-side camera, a display unit that is provided inside a vehicle cabin, memory, and a processor that is coupled to the memory. The processor is configured so as to acquire a rear image that includes a first image of a vehicle rear side acquired by the rear camera, a second image of a vehicle rear right-side acquired by the rear right-side camera, and a third image of a vehicle rear left-side acquired by the rear left-side camera, acquire from the plurality of sensors relative positions of a target that is present in areas including the vehicle rear side, the vehicle rear right-side, and the vehicle rear left-side relative to a host vehicle, determine whether or not the acquired relative positions of the target are mutually consistent with each other in the plurality of sensors, display a single composite image that is created by combining the first image, the second image, and the third image at the display unit in a case in which it is determined that the relative positions of the target are mutually consistent with each other, and display the first image, the second image, and the third image individually and adjacently to each other on the display unit in a case in which it is determined that the relative positions of the target are not mutually consistent with each other.

Vehicle-mounted camera pose estimation methods, apparatuses, and systems, and electronic devices involve performing lane line detection of a road on which a vehicle drives on the basis of a video stream of the road acquired by a vehicle-mounted camera; obtaining horizon information of the road on which the vehicle drives according to a lane line detection result; and obtaining pose information of the vehicle-mounted camera according to the horizon information.

A vehicular camera calibration system includes a camera disposed at a vehicle, and an electronic control unit (ECU). The camera calibration system utilizes an intrinsic parameter of the camera and uses a kinematic model of motion of the vehicle that is determined at least in part via processing of multiple frames of captured image data. The camera calibration system, responsive to processing of multiple frames of image data captured by the camera as the vehicle moves along a path of travel, and based at least in part on (i) an intrinsic parameter of the camera and (ii) the kinematic model of motion of the vehicle, determines misalignment of the camera. The camera calibration system determines camera misalignment without use of a fiducial marker in the field of view of the camera as the vehicle moves along the path of travel and without use of reference points on the vehicle.