Methods, apparatus, systems, and articles of manufacture are disclosed to calibrate a stereo camera. An example apparatus includes means for determining a motion grid between a first image and a second image captured by the stereo camera; means for determining a calibration value to calibrate the stereo camera based on a prior calibration value, a relative orientation between the first image and the second image based on the motion grid, and a metric indicative of calibration improvement; and means for estimating a depth based on the calibration value.

A method operable by circuitry including an image processor, an image sensor, and another clock-dependent device, including measuring a flicker using the image sensor, adjusting a clock rate of the circuitry according to the measured flicker, and operating the clock-dependent device using the adjusted clock rate.

A camera parameter derivation apparatus for deriving camera parameters of a plurality of cameras for which conditions that the cameras be arranged at ideal positions that are set on a straight line at equal intervals and that directions of all arranged cameras be parallel to each other have been set includes an internal parameter derivation unit that derives internal parameter matrices of the cameras based on estimated internal parameter matrices for all cameras that are arranged at estimated positions while being oriented in estimated directions, a camera position derivation unit that derives ideal positions of the cameras that minimize the maximum of the distances between the estimated positions and the ideal positions, and a rotation matrix derivation unit that derives rotation matrices for correcting external parameters such that errors from parallel directions are equal to or less than a threshold value.

An image capture system is configured to align a field of view of the image capture component with a field of view of a user of the system. In some cases, the image capture system may adjust the field of view of the image data based at least in part on orientation and position data associated with the capture device.

Examples are disclosed that relate to displaying a hologram via an HMD. One disclosed example provides a method comprising obtaining depth data from a direct-measurement depth sensor included in the case for the HMD, the depth data comprising a depth map of a real-world environment. The method further comprises determining a distance from the HMD to an object in the real-world environment using the depth map, obtaining holographic imagery for display based at least upon the distance, and outputting the holographic imagery for display on the HMD.

A multi-mode three-dimensional scanning method includes: obtaining intrinsic parameters and extrinsic parameters of a calibrated camera in different scanning modes, and upon switching between the different scanning modes, triggering a change of parameters of the camera to the intrinsic parameters and the extrinsic parameters in a corresponding scanning mode; and a user selecting to execute a laser-based scanning mode, a speckle-based scanning mode or a transition scanning mode according to a scanning requirement. In the continual fusion and conversion during the whole scanning process, the speckle reconstruction and the laser line reconstruction are unified to the same coordinate system, and the surface point cloud of the object being scanned is output. The present disclosure also provides a multi-mode three-dimensional scanning system.

A system for depth estimation, comprises at least a first and a second depth estimation optical systems, each configured for receiving a light beam from a scene and estimating depths within the scene, wherein the first system is a monocular depth estimation optical system; and an image processor, configured for receiving depth information from the first and second systems, and generating a depth map or a three-dimensional image of the scene based on the received depth information.

The present invention provides a method for correcting an anomalous pixel and an apparatus. The method for correcting the anomalous pixel comprises: calculating a matching index of pixels in a first point cloud map and a second point cloud map; finding out an anomalous pixel based on the matching index of the pixels and a correction threshold; and calculating a correction column difference, and correcting the anomalous pixel based on the correction column difference and the matching index of the pixels. The anomalous pixel in the point cloud map is retained and corrected, thus the pixel integrity of an image is guaranteed; and a mode for correcting the anomalous pixel is simple, requires fewer calculating steps, and exhibits high anomalous pixel correction efficiency. The apparatus provided by the present invention comprises a first camera, a second camera, an image processing unit, an indexing unit, a calculating unit, a judging unit, and a correction execution unit, and is used for improving the efficiency of correcting an anomalous pixel in an image.

A vehicle external environment imaging apparatus includes imaging devices and a controller. The imaging devices are disposed on a vehicle to perform imaging of a vehicle external environment. The controller generates information regarding a distance or a direction of a vehicle-external imaging target with imaging images of the imaging devices. At least two imaging devices are disposed on the vehicle to be able to perform duplicated imaging of a common imaging region. The controller generates, on the basis of a distance and a direction in an imaging image obtained by a first one of the at least two imaging devices, correction information regarding a distance, a direction or both of the vehicle-external imaging target based on an imaging position which is to be used in a monocular process on an imaging image of at least one the at least two imaging devices that is different from the first one.

A system and method for determining a dimension of a target. The method includes: determining a camera parameter, the camera parameter including at least one of a focal length, a yaw angle, a roll angle, a pitch angle, or a height of one or more cameras; acquiring a first image and a second image of an target captured by the one or more cameras; generating a first corrected image and a second corrected image by correcting the first image and the second image; determining a parallax between a pixel in the first corrected image and a corresponding pixel in the second corrected image; determining an outline of the target; and determining a dimension of the target based at least in part on the camera parameter, the parallax, and the outline of the target.