An apparatus includes a reference coordinate selection unit configured to select reference coordinates of two points from a focus frame area set by a setting unit, and determines arrangement intervals of focus frames based on coordinates on image data before correction corresponding to the coordinates selected by the reference coordinate selection unit and a number of focus frames.

A solution to the problem of image and video stitching is disclosed that compensates for the effects of lens distortion, camera misalignment, and parallax in combining multiple images. The disclosed image stitching technique includes depth or disparity estimation, alignment, and blending processes configured to be computationally efficient and produce quality results by limiting the presence of noticeable seams and artifacts in the final stitched image. An inter-frame approach applies image stitching to video frames to maintain temporal continuity between successive frames across a stitched video output having a 360-degree viewing perspective. A temporal adjustment is configured to improve temporal continuity between a subsequent frame and a previous frame in a sequence of video frames.

Provided are an image rectification method and apparatus, and an electronic system. The image rectification method includes: acquiring a first image and a second image of the same shooting object by means of a first shooting apparatus and a second shooting apparatus which are coaxially disposed; and correcting the second image according to shooting parameters of the first shooting apparatus and the second shooting apparatus to obtain a second rectified image, such that the parallax between the second rectified image and the first image in a vertical direction or a horizontal direction is zero. In the method, by taking a first image as a reference, and by means of adjusting the shooting parameters of the first shooting apparatus and a second shooting apparatus, only the second image is rectified, thereby improving the operation efficiency of image rectification, and improving the accuracy and stability of an image rectification result.

An object detection vision system and methods are disclosed. A method for detecting objects in a vision system of an industrial machine includes receiving image data from one or more vision cameras and receiving detection data from one or more detect devices. The detection data includes one or more detected objects. The method includes combining the detection data and the image data and transforming the detection data in the image data based on one or more objects in the image data. The method also includes displaying an indication of the detected one or more objects in the image data based on the transformed detection data.

An image calibration method applied to a wide-angle image and executed by an image calibration apparatus includes applying primary lens distortion correction for the wide-angle image to generate a corrected image, segmenting an foreground image from the corrected image to generate a background image, applying secondary distortion correction for the foreground image based on the pre-defined object to generate a calibrated foreground image, fusing the background image with the calibrated foreground image to generate a fused image, detecting at least one residual empty pixel not overlapped by the calibrated foreground image within the fused image, and utilizing a machine learning algorithm to fill the at least one residual empty pixel of the fused image by extending the background image to provide an output image. The foreground image contains feature pixels relate to a pre-defined object and the background image has empty pixels corresponding to the foreground image.

A computer-implemented method for displaying augmented reality (AR) content within an AR device coupled to one or more loupe lenses comprising: obtaining calibration parameters defining a magnified display portion within a display of the AR device, wherein the magnified display portion corresponds to boundaries encompassing the one or more loupe lenses; receiving the AR content for display within the AR device; and rendering the AR content within the display, wherein the rendering the AR content comprises: identifying a magnified portion of the AR content to be displayed within the magnified display portion, and rendering the magnified portion of the AR content within the magnified display portion.

[Object] To provide a display apparatus, an image generation method, and a program that are capable of displaying images such that an image displayed on a display unit and a scene outside the display apparatus appear to be continuous.

[Solving Means] The display apparatus includes a first image sensor, a first distance sensor, a second sensor, a display unit, and an image generation unit. The first image sensor is disposed on a first surface side of an apparatus main body. The first distance sensor is disposed on the first surface side. The second sensor is disposed on a second surface side opposite to the first surface side. The display unit is disposed on the second surface side. The image generation unit generates a display image to be displayed on the display unit, using a two-dimensional image of a subject and a distance image of the subject, the two-dimensional image being acquired by the first image sensor, the distance image being acquired by the first distance sensor, on the basis of three-dimensional position information of a viewpoint of a photographer, the three-dimensional position information being calculated on the basis of a sensing result acquired by the second sensor.

In one embodiment, there is provided an apparatus for low-dimensional manifold constrained disentanglement for metal artifact reduction (MAR) in computed tomography (CT) images. The apparatus includes a patch set construction module, a manifold dimensionality module, and a training module. The patch set construction module is configured to construct a patch set based, at least in part on training data. The manifold dimensionality module is configured to determine a dimensionality of a manifold. The training module is configured to optimize a combination loss function comprising a network loss function and the manifold dimensionality. The optimizing the combination loss function includes optimizing at least one network parameter.

One disclosed example provides a videoconferencing system comprising a processor and a storage device storing instructions executable by the processor to obtain an image of a scene acquired via a camera, the image of the scene comprising image distortion arising from a camera pitch angle at which the image of the scene was acquired. The instructions are further executable to apply a projection mapping to the image of the scene to map the image of the scene to a projection comprising a tilt parameter that is based upon the camera pitch angle at which the image of the scene was acquired, thereby obtaining a corrected image, and output the corrected image.

An electronic device includes a UDC and a UDC controller configured to determine an optimal number of frames required to be captured for a scene to compensate at least one parameter to optimize an output media using the UDC, obtain a multi-frame fusion media by performing at least one multi-frame fusion on the determined optimal number of frames, perform a light source spread correction on the multi-frame fusion media, and optimize the output media based on the light source spread correction on the multi-frame fusion media.