An image processing device 10 includes an image interface 18, a memory 19, and a controller 20. The image interface 18 acquires a captured image. The positions of specific feature points in a world coordinate system and reference positions of the specific feature points are stored in the memory 19. The controller 20 detects the specific feature points in the captured image. In a case where discrepancy between the position in the captured image and the reference position is found with regard to a predetermined percentage or more of the specific feature points, the controller 20 recalculates a calibration parameter.

A method includes the steps of arranging mark points for image recognition on a plane of a test piece to be measured; recognizing and recording positions of two-dimensional Cartesian coordinates of each mark point of the test piece to be measured before and after each stretching; and determining a deformation gradient of each mark point and deformation measurement parameters of each mark point through a numerical method, where the deformation measurement parameters include a deformation gradient matrix, an elongation tensor matrix, a finite strain tensor matrix, an orthogonal tensor matrix, an angular tensor matrix, a rotation angle, and a curvature. According to the method, objective measurement of super-large deformation of the plane relating to rotation deformation is achieved.

An information processing apparatus comprises a first acquisition unit that acquires a captured image obtained by capturing an image of a chart for calibration, a second acquisition unit that acquires a reference image which is an image of the chart that serves as a reference, a third acquisition unit that acquires information on distortion aberration of a lens used to capture the captured image, a first generation unit that generates a pseudo image which is an image obtained by reflecting the distortion aberration in the reference image, based on the reference image and the information on distortion aberration, and a second generation unit that generates a composite image obtained by compositing the captured image and the pseudo image.

A program executed by a processor causes the processor to identify, based on a result of an image captured by a first camera configured to capture an image of a user in a real space, a position of the user; display, based on the result of the image captured by the first camera, on a display, a first image representative of the user; and display, at a position that is based on an identification result obtained by identifying the position of the user, a second image that corresponds to an object in the real space.

Techniques for calibrating cameras and displays are disclosed. An image of a target is captured using a camera. The target includes a tessellation having a repeated structure of tiles. The target further includes unique patterns superimposed onto the tessellation. Matrices are formed based on pixel intensities within the captured image. Each of the matrices includes values each corresponding to the pixel intensities within one of the tiles. The matrices are convolved with kernels to generate intensity maps. Each of the kernels is generated based on a corresponding unique pattern of the unique patterns. An extrema value is identified in each of the intensity maps. A location of each of the unique patterns within the image is determined based on the extrema value for each of the intensity maps. A device calibration is performed using the location of each of the unique patterns.

A picture processing method includes: identifying a target area where a QR code is located in a picture; obtaining parameters of the picture; and performing effacing process on the target area of the picture based on the parameters.

Disclosed are a method and system for testing a wearable device. The method includes: performing an angle acquisition process for at least two times, and calculating an optical imaging parameter value of a target virtual image on the basis of angle variation values acquired in the at least two angle acquisition processes. With the method and system according to the present disclosure, the finally calculated optical imaging parameter value is more objective and more accurate than that acquired by means of the human eyes.

A system and method for head tracking for a head worn display (HWD) includes head-frame and platform-frame IMUs providing high-rate pose data of the wearer's head and a mobile platform. An optical tracker estimates an optical pose of a camera oriented at fiducials based on a comparison of 2D image data captured by the camera (and portraying the fiducials within the image) and the known location of each fiducial in a 3D marker frame. The pIMU also provides low-rate, high-integrity georeferenced pose data of the mobile platform (e.g., in an earth frame). The head tracker provides low-rate, high-integrity absolute head pose solutions (e.g., user head pose in the earth frame) based on the georeferenced pose data and current high-rate head/platform pose data, updating the absolute pose solutions with high-rate updates based on combined extended Kalman filter propagation of the high-rate head and platform pose data with refined optical pose data.

A real-time pose measurement method of a planar coding target for a vision system. The planar coding target includes a plurality of coding elements, a coding block, a coding template, a minimum identification unit pattern and a coding pattern. Each coding element has a unique coding value, and serial numbers of the coding elements are different from each other. The coding block includes four coding elements that are distributed in the same rectangle ABCD and do not overlap with each other. A center of the coding block is an intersection point O of two diagonals of the rectangle ABCD. A coding value of the coding block is associated with coding values of the four coding elements contained therein.

An article of manufacture may include a matrix barcode on a physical medium and associated with an environment. The matrix barcode may include a plurality of colors, where at least one of the plurality of colors is a least prevalent color, of a plurality of prevalent colors in the environment.