Discussed herein are devices, systems, and methods for multi-image ground control point (GCP) determination. A method can include extracting, from a first image including image data of a first geographical region, a first image template, the first image template including a contiguous subset of pixels from the first image and a first pixel of the first image indicated by the GCP, predicting a first pixel location of the GCP in a second image, the second image including image data of a second geographical overlapping with the first geographical region, extracting, from the second image, a second image template, the second image template including a contiguous subset of pixels from the second image and a second pixel corresponding to the pixel location, identifying a second pixel of the second image corresponding to a highest correlation score, and adding a second pixel location of the identified pixel to the GCP.

The disclosure provides an interactive projection system and an interactive display method of the projection system. The interactive projection system includes a biologically-modeled housing, a first projection device disposed inside the biologically-modeled housing and an interactive sensing device, and a controller. The biologically-modeled housing includes a light-transmissive curved projection area. The first projection device projects the first physiological image onto the curved projection area. The interactive sensing device obtains the input signal. The controller is electrically connected to the first projection device and the interactive sensing device to identify the input signal and obtain user instructions. The controller controls the first projection device to project the second physiological image to the curved projection area according to user instructions. The first physiological image and the second physiological image display the physiological features corresponding to the curved projection area at a position on the biologically-modeled housing.

In an aspect, an image processing apparatus includes a processor and a memory in which a plurality of images obtained by capturing images of a building and a three-dimensional model of the building are stored in association with each other. The processor is configured to perform a development process to perform development of the three-dimensional model into a two-dimensional image, an extraction process to extract defect information of the building on the basis of the plurality of images, a mapping process to perform mapping of the defect information to the two-dimensional image, and an output process to output the two-dimensional image to which the mapping is performed.

A method for processing images includes: determining a plurality of first key points in a first image; determining a target region of the first image, wherein the target region is acquired by expanding a region corresponding to the plurality of first key points; and acquiring a second image by adjusting a target part based on the region corresponding to the plurality of first key points and the target region.

A framework for multi-scan image processing. A single real anatomic image of a region of interest is first acquired. One or more emission images of the region of interest are also acquired. One or more synthetic anatomic images may be generated based on the one or more emission images. One or more deformable registrations of the real anatomic image to the one or more synthetic anatomic images are performed to generate one or more registered anatomic images. Attenuation correction may then be performed on the one or more emission images using the one or more registered anatomic images to generate one or more attenuation corrected emission images.

An Artificial Intelligence (Al) three-dimensional modeling system that analyzes and segments imagery of a room, generates a three-dimensional model of the room from the segmented imagery, identifies objects within the room, and conducts an assessment of the room based on the identified objects.

An Artificial Intelligence (Al) three-dimensional modeling system that analyzes and segments imagery of a room, generates a three-dimensional model of the room from the segmented imagery, identifies objects within the room, and conducts an assessment of the room based on the identified objects.

Embodiments of the present disclosure provide a facial image deformation method and apparatuses, an electronic device, and a computer-readable media. A specific embodiment of the method comprises: determining an anchor point corresponding to a dragging operation in response to detecting the dragging operation on a target facial image, wherein the anchor point corresponds to a part displayed in the target facial image; determining an offset of the anchor point based on a movement amount corresponding to the dragging operation; and deforming the target facial image based on the offset of the anchor point.

Systems and methods are described for receiving a plurality of input images, a plurality of depth images, and a plurality of view parameters for generating a virtual view of a target subject. The systems and methods may generate a plurality of warped images based on the plurality of input images, the plurality of view parameters, and at least one of the plurality of depth images. In response to providing the plurality of depth images, the plurality of view parameters, and the plurality of warped images to a neural network, the systems and methods may receive, from the neural network, blending weights for assigning color to pixels of the virtual view of the target subject and may generate, based on the blending weights and the virtual view, a synthesized image according to the view parameters.

A method for dewarping a region of a fisheye view image , captured by a fisheye lens wherein the fisheye view image comprises a first dewarping pole, DP1. The method defines a region of interest, ROI, determining a center, G, of the ROI, defining a temporary annulus sector region such that the temporary annulus sector region comprises the ROI, and has its center at DP1 and has a temporary outer arc shaped edge and a temporary inner arc shaped edge, defining a second dewarping pole, DP2 at a distance, D, from DP1 along a radial direction extending from G of the ROI through the DP1, setting a dewarping annulus sector region comprising the ROI. The dewarping annulus sector region has its center at DP2 and has its dewarping inner arc shaped edge maintained at a same radial distance from DP1 as the temporary inner arc shaped edge.