An electronic device for synthesizing an image, and an operating method thereof, are provided. The electronic device may include a display, a processor operatively coupled to the display, and a memory operatively coupled to the processor, wherein the memory may store instructions, which when executed, cause the processor to identify at least one target object in a first image, and at least one background object in a second image, determine a position for arranging the at least one target object on the second image, based on correlation of the at least one identified target object and the at least one identified background object, obtain a third image by arranging the at least one target object based on the determined position on the second image, and display the obtained third image on the display.

A system produces a dolly zoom effect by utilizing side view information. The system first captures a main image at a main location. The main image includes at least a foreground object of a given size and a background. The system calculates one or more side view locations based on a zoom-in factor to be applied to the background and an estimated size of the foreground object. The system then guides a user to capture one or more side view images at the one or more side view locations. The foreground object of the given size is superimposed onto a zoomed-in background. Then the side view information is used by the system to perform image inpainting.

The present invention has an object to provide a virtual reality video reproduction apparatus that can allow a viewer to experience an impairment due to a disease, such as diabetes, with a strong sense of immersion. The virtual reality video reproduction apparatus of the present invention applies a filter process of simulating a visual impairment caused by diabetes to a predetermined area of images included in a virtual reality video that represents virtual reality content, and causes an electronic display included in a virtual reality headset to display the video.

A method and system for processing an image is described. For example, the method comprises detecting a plurality of objects within an in input image; identifying dimensions of a display on which the input image is to be displayed; cropping the input image to obtain a cropped image which matches the identified dimensions, wherein the cropped image includes at least one of the plurality of detected objects; obtaining a list of missing objects which are not visible in the cropped image and which were detected in the input image; outputting a representation of each missing object in the list of missing objects to be displayed together with the cropped image; generating an updated image comprising the representation of at least one missing object and which matches the identified dimensions; and outputting the updated image to be displayed on the display.

A method for identifying, locating, and mapping targets of interest using unmanned aerial vehicle (UAV) camera footage in GPS-denied environments. In one embodiment, the method comprises obtaining UAV visual data, passing the UAV visual data through a convolutional neural network (CNN) in order to detect targets of interest based on visual features disposed in the UAV visual data, wherein the detection by the CNN defines reference points and pixel coordinates for the UAV visual data, applying a geometric transformation to known and defined pixel coordinates to obtain real-world orthogonal positions; and projecting the detected targets of interest onto an orthogonal map based on the obtained real-world orthogonal positions, all without GPS data.

An image processing apparatus includes a processor configured to: display an image on a display device; calculate, for each of small regions set in the image, a degree of importance based on characteristics of the image; and display a degree-of-importance map on the display device in such a manner that the degree-of-importance map is superimposed on a subject region of the image, the degree-of-importance map visually representing a relative relationship between the degrees of importance of the small regions.

A method of detecting a protrusion in an intestinal tract in a computer according to an embodiment of the present disclosure includes acquiring a three-dimensional model of the intestinal tract scanned by a scanning device, the three-dimensional model comprising three-dimensional data of the intestinal tract; mapping, in the computer, the three-dimensional model to a two-dimensional plane in an area-preserving manner; and detecting an area of the protrusion in the two-dimensional plane. The method can replace traditional modes such as enteroscopy, and the protrusion in the intestinal tract is detected in a painless and low-cost mode.

Some embodiments of the present disclosure may relate to an image processing system and method. The image processing system and method may include: obtaining an initial image; determining, based on the initial image, a plurality of to-be-processed images related to the initial image; and processing the plurality of to-be-processed images based on a processing model to obtain a target image of the initial image.

A method and a device for 3D shape matching based on a local reference frame are proposed. After acquiring a 3D point cloud and feature points in the method, the feature point set is projected to a plane, and feature transformation is performed on the projected points by using at least one factor from the distances between the 3D points and the feature points, the distances between the 3D points and the projected points, and the average distances between the 3D points and its 1-ring neighboring points to acquire a point distribution with a larger variance in a certain direction than the projected point set, and the local reference frame is determined based on the transformed point distribution. The 3D local feature descriptor established based on this local reference frame can encode the 3D local surface information more robustly, so as to obtain a better 3D shape matching effect.

A camera system and method are disclosed. The camera includes a memory, a camera, and a processor. The memory stores an adaptively subsampled look-up table. The adaptively subsampled look-up includes varying levels of subsampling across the adaptively subsampled look-up table. The camera captures an image, and the captured image is distorted based on varying distortions within an optical system of the camera. The processor receives the captured image from the camera, corrects the distorted captured image based on the adaptively subsampled look-up table to create a correct image, provides the corrected image, and executes a safety feature based on the corrected image.