17 results about "Spherical image" patented technology

A system may obtain a plurality of experimental diffraction patterns. A system may identify a crystallographic orientation of each diffraction pattern of the plurality of experimental diffraction patterns. A system may build one or more pole figures. A system may select a reference spherical function having a reference frame. A system may correlate spherical images from the pole figures and the reference spherical function. A system may determine a sample frame of the crystallographic orientations. A system may rotate the crystallographic orientations of the plurality of experimental diffraction patterns into alignment with the reference frame to produce a plurality of rotated crystallographic orientations.

Obtaining a processed spherical image includes obtaining a first luminance thumbnail image for a first hemispherical input image, obtaining a second luminance thumbnail image for a second hemispherical input image, obtaining a first distortion correcting weight map, obtaining a second distortion correcting weight map, obtaining, as an aggregate weighted mean value for the input spherical image, an aggregate of a first normalized weighted mean value for the first luminance thumbnail image and a second normalized weighted mean value for the second luminance thumbnail image, obtaining at least one of a target exposure value, a target aggregate gain value, or a region of interest ratio value in accordance with the aggregate weighted mean value, and obtaining the processed spherical image from the input spherical image in accordance with at least one of the target exposure value, the target aggregate gain value, or the region of interest ratio value.

Obtaining a processed spherical image includes obtaining a first luminance thumbnail image for a first hemispherical input image, obtaining a second luminance thumbnail image for a second hemispherical input image, obtaining a first distortion correcting weight map, obtaining a second distortion correcting weight map, obtaining, as an aggregate weighted mean value for the input spherical image, an aggregate of a first normalized weighted mean value for the first luminance thumbnail image and a second normalized weighted mean value for the second luminance thumbnail image, obtaining at least one of a target exposure value, a target aggregate gain value, or a region of interest ratio value in accordance with the aggregate weighted mean value, and obtaining the processed spherical image from the input spherical image in accordance with at least one of the target exposure value, the target aggregate gain value, or the region of interest ratio value.

Embodiments of the present specification provide a panoramic image processing method and device, the method comprising inputting a target panoramic image into an image processing model, obtaining panoramic image features of the target panoramic image through an encoding layer of the image processing model; converting the panoramic image features into spherical image encoding features according to a panoramic image spherical conversion algorithm; inputting the spherical image encoding features into a decoding layer of the image processing model, and obtaining a spherical depth image of the target panoramic image through the decoding layer; and converting the spherical depth image into a panoramic depth image of the target panoramic image according to the panoramic image spherical conversion algorithm. The method obtains a depth image of a panoramic image by using an image processing model, saves costs without additional instruments and equipment; and runs an image processing model specially designed for a sphere on a sphere, solves distortion generated in an ERP projection process of a panoramic image, and improves the accuracy of obtaining a depth image of a panoramic image.

Various aspects of visual servoing based on use of a generative diffusion model are described. One technique includes obtaining a current view image from a robot camera that captures a portion of an environment of the robot, and obtaining a spherical image from a previous view that depicts a surrounding area of the environment of the robot. The current view image is combined with the previous spherical image to produce a modified spherical image, and inpainting is performed in a mask area of the modified spherical image with a generative diffusion model. The inpainting blends the current view image with the previous spherical image, providing a view of the entire environment of the robot that can be used for visual servoing. The robot can perform path planning and visual servoing of an end effector based on the modified spherical image, independent of any use of an external positioning or localization system.

The present application is applicable to the technical field of image processing, and provides an image stitching method, applied to a panoramic camera. The panoramic camera is provided with a first fisheye lens and a second fisheye lens. The image stitching method comprises: acquiring a first fisheye image by means of the first fisheye lens, and acquiring a second fisheye image by means of the second fisheye lens (S101); mapping the first fisheye image onto a unit spherical surface to obtain a first spherical image, and mapping the second fisheye image onto the unit spherical surface to obtain a second spherical image (S102); rotating the first spherical image by a specified angle to obtain a rotated first spherical image, and rotating the second spherical image by the specified angle to obtain a rotated second spherical image (S103); unwrapping the rotated first spherical image into a first ERP image, and unwrapping the rotated second spherical image into a second ERP image (S104); and stitching the first ERP image and the second ERP image to obtain a target image (S105). Thus, the image stitching accuracy is effectively improved.

The present application relates to a method, system and non-transitory computer readable recording medium for correcting luminance of a spherical image. According to an aspect of the present application, there is provided a method for correcting luminance of a spherical image, comprising: calculating a photographing luminance distribution of a region corresponding to a sphere as a physical quantity measurement object in a plurality of images photographed with respect to the sphere; and correcting the photographing luminance distribution of the region corresponding to the sphere in at least one of the plurality of images with reference to a reference luminance distribution.

A spherical image compression method and device based on a spherical depth neural network are disclosed.The present application is based on the resampling of a spherical image based on a spherical measure,uniformly samples the spherical image using SMSIR,designs a basic component for learning a spherical image,through the integration of spherical convolution and self-attention spherical transformation,models the code rate using a spherical entropy model,so as to solve the problem of low efficiency of traditional spherical compression methods.

This invention provides a method and system for super-resolution of spherical signals, comprising: constructing a parameterized spherical icosahedral triangular mesh; projecting an equidistant rectangular projection image (ERP) from two-dimensional space onto the icosahedral triangular mesh to obtain a spherical mesh signal; passing the spherical mesh signal through a first feature extractor to obtain a first multi-scale feature; passing the first multi-scale feature through a second feature extractor to obtain a second multi-scale feature; expanding the second multi-scale feature based on an adaptive filter learning of Chebyshev polynomials and spherical pixel recombination to obtain spherical mesh expanded features; reconstructing the upsampled spherical mesh signal; and inversely projecting the upsampled spherical mesh signal onto the ERP to obtain a super-resolution spherical image. This invention enables high-quality representation learning and detail characterization of low-resolution spherical image inputs, especially in ultra-high magnification image super-resolution tasks, generating super-resolution spherical images with more complete details and less distortion.

Various aspects of visual servoing based on use of a generative diffusion model are described. One technique includes obtaining a current view image from a robot camera that captures a portion of an environment of the robot, and obtaining a spherical image from a previous view that depicts a surrounding area of the environment of the robot. The current view image is combined with the previous spherical image to produce a modified spherical image, and inpainting is performed in a mask area of the modified spherical image with a generative diffusion model. The inpainting blends the current view image with the previous spherical image, providing a view of the entire environment of the robot that can be used for visual servoing. The robot can perform path planning and visual servoing of an end effector based on the modified spherical image, independent of any use of an external positioning or localization system.

The embodiment of the utility model relates to the technical field of fisheye lenses, in particular to a full-spherical fisheye lens. The full-spherical fisheye lens sequentially comprises a front lens group, a middle lens group and a rear lens group from an object side to an image side along an optical axis, the front lens group sequentially comprises a first lens with negative focal power, a second lens with negative focal power, a third lens with negative focal power, a fourth lens with positive focal power and a fifth lens with negative focal power from the object side to the image side along the optical axis; the middle lens group sequentially comprises a sixth lens with negative focal power and a seventh lens with positive focal power from the object side to the image side along the optical axis; the rear lens group sequentially comprises an eighth lens with positive focal power from the object side to the image side along the optical axis. The full spherical fisheye lens with the structure can achieve a larger maximum half field angle, the image quality of a spherical image projected by the full spherical fisheye lens also has higher definition, and the optical structure of the full spherical fisheye lens is also simpler.

The invention belongs to the technical field of panoramic image information enhancement, and discloses a terrain intervisibility information enhancement expression method and a terrain intervisibility information enhancement expression system in an aerial panoramic image. Converting the two-dimensional coordinates into spherical longitude and latitude coordinates, converting the spherical longitude and latitude coordinates into ground point spherical image space coordinates in combination with image depth information, converting panoramic image pose data into ground point space rectangular coordinates, calculating intervisibility information, and differentially expressing intervisibility and non-intervisibility areas according to colors; and returning the coordinate value with the intervisibility color information to the corresponding panoramic image to realize topographic feature fusion expression. The intervisibility relationship enhancement expression is concise and clear, the rendered curved surface is accurately matched with the image scene, and a certain three-dimensional effect is achieved; through comprehensive research and judgment of an intervisibility relationship analysis result and a real scene of an analysis area, an on-site environment condition can be better understood.

This invention discloses a method for feature matching of spherical panoramic images, comprising: acquiring spherical panoramic images in ERP format; extracting features from the ERP format spherical panoramic images and generating a first feature descriptor; performing local image patch geometric correction on the ERP format spherical panoramic images using image patch reprojection; generating a second feature descriptor with the same dimension as the first feature descriptor using a CNN based on the corrected image patches; performing initial feature matching on two spherical panoramic images based on the second feature descriptor; and optimizing the initial feature matching using coplanar geometric constraints. This invention designs and implements a reliable spherical image feature matching algorithm by combining local geometric correction with descriptors learned by CNN.

Various implementations disclosed herein include devices, systems, and methods that provides augmented spherical image content based on detected attributes. For example, an example process may include obtaining a spherical image content (e.g., captured 180° / 360° / surround video content) generated using a combination process that combines images that were captured within a particular time period by a multi-camera configuration, the multi-camera configuration includes a plurality of cameras oriented in different respective orientations, and the time period is below a threshold. The process may further include determining an attribute of the spherical image content corresponding to the multi-camera configuration or the combination process, generating virtual content based on the determined attribute, wherein at least a portion of the virtual content is configured to be congruent with the attribute of the spherical image content, and generating augmented spherical image content based on the spherical image content and the virtual content.

The application discloses a panoramic image generation method and device, a terminal and a storage medium. The method comprises the following steps: determining a first spherical image and a second spherical image based on a first image, a second image and a preset spherical coordinate system; determining pixel values of all points on the first spherical image and pixel values of all points on the second spherical image based on the first spherical image and the second spherical image respectively; determining a pitch angle offset and a direction angle offset corresponding to the first spherical image and the second spherical image based on a first preset method, the pixel values of all points on the first spherical image and the pixel values of all points on the second spherical image; and performing splicing and fusion on the first spherical image and the second spherical image based on the pitch angle offset and the direction angle offset to generate a panoramic image. The application selects pixel values of overlapping areas according to the confidence degree of the overlapping areas, thereby ensuring the accuracy of the panoramic image after splicing and fusion and improving the efficiency of image splicing.

Embodiments of the application disclose a camera group calibration method, device, equipment and medium, and relate to the technical field of camera calibration. The method comprises: acquiring a calibration object image of a to-be-calibrated object in a candidate camera coordinate system, and determining candidate calibration object coordinates in the candidate camera coordinate system according to the calibration object image; determining whether the candidate camera coordinate system is a reference camera coordinate system, and if not, converting the candidate calibration object coordinates in the candidate camera coordinate system into reference calibration object coordinates in the reference camera coordinate system according to a preset camera group transformation matrix; determining corresponding calibration compensation data according to the reference calibration object coordinates and a preset calibration error function, and determining target calibration object coordinates of the to-be-calibrated object according to the reference calibration object coordinates and the calibration compensation data; wherein the calibration error function is determined based on a spherical image of a calibration sphere at different acquisition positions in a field of view overlap region of the camera group and a preset sphere radius. The spatial consistency and robustness of camera group calibration are improved.