36 results about "Texture space" patented technology

Example embodiments relate to techniques for volumetric performance capture with neural rendering. A technique may involve initially obtaining images that depict a subject from multiple viewpoints and under various lighting conditions using a light stage and depth data corresponding to the subject using infrared cameras. A neural network may extract features of the subject from the images based on the depth data and map the features into a texture space (e.g., the UV texture space). A neural renderer can be used to generate an output image depicting the subject from a target view such that illumination of the subject in the output image aligns with the target view. The neural render may resample the features of the subject from the texture space to an image space to generate the output image.

Methods, systems and apparatuses may provide for technology that determines a major axis length of an ellipse in texture space based on a transformation matrix associated with a circle in screen space, inverts the major axis length, determines a product between the inverted major axis length and a determinant of the transformation matrix, and determines a minor axis length based on a modulus of the product between the inverted major axis length and the determinant of the transformation matrix. In one example, the technology selects a level of detail in the texture space based on the major axis length, the minor axis length, a direction of the major axis length, and a direction of the minor axis length.

The invention discloses a pixel-level accurate texture generation method based on a multi-view artistic work. The method comprises the following steps: inputting an image file; performing multi-view projection on the 3d model for a plurality of views corresponding to the plane image to construct a texture space; aiming at coexisting points on the surface of the 3d model in the multiple visual angles, calculating a dot product of each visual angle direction and a normal of the surface of the 3d model so as to construct an initial texture map corresponding to the 3d model; projecting all contour points of the 3d model into a texture space to obtain corresponding texture information, and comparing the texture information with contour points contained in the initial texture map to construct a mask area; generating a shielding texture map corresponding to the mask area through a diffusion model; and carrying out rendering processing on the 3d model based on the initial texture map and the sheltered texture map so as to output a high-quality model with texture information. The invention further provides a pixel-level accurate texture generation device. According to the method provided by the invention, the high-quality texture can be generated for the grid, and meanwhile, the pixel-level consistency with the reference art is ensured.

This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for a dicing oracle for texture space shading. A processor obtains an indication of a UV parameterization for each of a set of geometry units and a target number of pixels per region of the UV parameterization, where the UV parameterization includes a first set of UV coordinates for an object space. The processor renders the set of geometry units in order to obtain a second set of UV coordinates for a screen space and a set of derivatives for the second set of UV coordinates. The processor calculates a resolution for a mip region map based on the set of derivatives and the target number of pixels per region. The processor outputs an indication of the calculated resolution.

According to an embodiment, a method for generating a digital three-dimensional model representing development in dental condition for a tooth is disclosed. The method includes obtaining, at different timepoints, a first digital 3D model of a patient's set of teeth including first texture data and a second digital 3D model of the patient's set of teeth including second texture data. The first digital 3D model including the first texture data and second digital 3D model including the second texture data are placed in a common texture space by uniformizing texture. Lastly, the digital three-dimensional model representing development in dental condition is generated based on a comparison of the first texture data and the second texture data of corresponding regions in the first digital 3D model and the second digital 3D model placed in the common texture space.

A rendering controller is provided for rendering light in a 3D scene that includes one or more objects, e.g., each object associated with a plurality of surface reservoirs. The rendering controller is also configured to provide optical transmission calculations in a texture space using the RIS or the WRS according to the surface cache. A rendering controller is used to efficiently compute shading (i.e., direct illumination and indirect illumination) of a 3D scene in a multi-viewer application involving complex illuminated scenes present in the cloud.

The invention relates to a graphics processor, an image processing method and electronic equipment, and relates to the technical field of image processing. The graphics processor comprises a gradient LOD calculation circuit and a shader. The LOD calculation circuit is used for obtaining the gradient LOD of a plurality of effective pixels in the image frame in the texture space, and the effective pixels are used for forming primitives in the image; and the shader is used for coloring the plurality of effective pixels according to the LOD of the plurality of effective pixels. Therefore, computing resources can be saved.

This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for sampler feedback for texture space shading. A processor may assign each shading element in a set of shading elements associated with a geometry unit to a corresponding shading element group in a set of shading element groups. The processor may identify whether each shading element is a visible shading element. The processor may calculate a group offset value for each shading element group in the set of shading element groups based on a number of visible shading elements in the set of shading elements. The processor may calculate an element offset value for each shading element based on a number of visible shading elements. The processor may allocate, based on the element offset value and the group offset value, texture memory to the visible shading elements.

A high-precision mapping method for an underground poor texture space based on mobile-fixed collaborative deviation correction includes: acquiring sensor data of sensor nodes determined based on the structure of the underground poor texture space; calculating the initial position data of an UAV; receiving sensor data through the UAV, and generating position data of the UAV by combining the initial position data of the UAV and lidar detection data of the UAV; correcting the position data of the UAV through a segmented mobile-fixed collaborative odometer; acquiring point cloud data for describing the structure of underground poor texture space; performing data fusion on the sensor data, the initial position data of the UAV, the corrected position data of the UAV and the point cloud data to obtain fused data, and establishing a high-precision map of the underground poor texture space, with each sensor node used as a feature point in the mapping.

A method of performing anisotropic texture filtering includes generating one or more parameters describing an elliptical footprint in texture space; performing isotropic filtering at each of a plurality of sampling points along a major axis of the elliptical footprint, wherein a spacing between adjacent sampling points of the plurality of sampling points is proportional to √{square root over (1−η−2)} units, wherein η is a ratio of a major radius of an ellipse to be sampled and a minor radius of the ellipse to be sampled, wherein the ellipse to be sampled is based on the elliptical footprint; and combining results of the isotropic filtering at the plurality of sampling points with a Gaussian filter to generate at least a portion of a filter result.

This invention discloses a visual localization method based on pose space texture continuity mapping, belonging to the fields of robotics and computer vision. In the mapping stage, image intrinsic parameters, pose, and sparse point cloud are first obtained through sparse reconstruction. Image features are extracted using a pre-trained model, and pose encoding and decoding models are trained to ensure consistency between pose encoding and image features in spatial metrics. Simultaneously, the decoding model outputs a multi-peak distribution to model pose ambiguity. Subsequently, a mapping model from image features to pose encoding is trained and optimized end-to-end to construct a scene map. In the localization stage, features of the image to be localized are extracted, pose encoding is obtained through the mapping model, and the pose distribution is output by the decoding model. A unique location or multiple candidate poses are determined based on the number of peaks in the distribution. This invention effectively improves the robustness and accuracy of robot localization in repetitive texture scenes by maintaining the continuity alignment between the pose space and texture space.

Example embodiments relate to techniques for volumetric performance capture with neural rendering. A technique may involve initially obtaining images that depict a subject from multiple viewpoints and under various lighting conditions using a light stage and depth data corresponding to the subject using infrared cameras. A neural network may extract features of the subject from the images based on the depth data and map the features into a texture space (e.g., the UV texture space). A neural renderer can be used to generate an output image depicting the subject from a target view such that illumination of the subject in the output image aligns with the target view. The neural render may resample the features of the subject from the texture space to an image space to generate the output image.

The invention relates to a real-time texture drawing method and system based on a lookup table, and the method comprises the steps: matching a texture space sampling point coordinate corresponding to each element obtained from a pre-constructed initial lookup table with a texture space vertex coordinate of each triangular primitive in an imported three-dimensional model; obtaining a triangular primitive matched with each element, obtaining a model space sampling point coordinate corresponding to each element according to the matched triangular primitive, and storing the model space sampling point coordinates corresponding to all the elements into an initial lookup table to obtain a final lookup table; according to drawing parameters input by a user, a drawing area is screened out from the final lookup table, texture color writing is conducted on the three-dimensional model according to texture space sampling point coordinates corresponding to elements existing in the drawing area, and real-time texture drawing is achieved. Therefore, accurate texture drawing is realized.

The application provides a kind of underground poor texture space high-precision mapping method based on solid displacement coordination rectification, relating to map construction technical field, method includes: obtaining the sensor data of sensor node based on the determination of underground poor texture space structure;Calculate the initial position data of unmanned aerial vehicle;Through unmanned aerial vehicle receives sensor data, and generate unmanned aerial vehicle position data in combination with initial position data of unmanned aerial vehicle and unmanned aerial vehicle laser radar detection data;Through segmented solid displacement coordination odometry, correct unmanned aerial vehicle position data;Obtain point cloud data for describing underground poor texture space structure;Sensor data, initial position data of unmanned aerial vehicle, corrected unmanned aerial vehicle position data and point cloud data are fused to obtain fusion data, and each sensor node is used as feature point in mapping process, and the high-precision map of underground poor texture space is established.The application can accurately establish the high-precision map of underground poor texture space, and effectively improve the efficiency of underground space management and application.

According to an embodiment, a method for generating a digital three-dimensional model representing development in dental condition for a tooth is disclosed. The method includes obtaining, at different timepoints, a first digital 3D model of a patient's set of teeth including first texture data and a second digital 3D model of the patient's set of teeth including second texture data. The first digital 3D model including the first texture data and second digital 3D model including the second texture data are placed in a common texture space by uniformizing texture. Lastly, the digital three-dimensional model representing development in dental condition is generated based on a comparison of the first texture data and the second texture data of corresponding regions in the first digital 3D model and the second digital 3D model placed in the common texture space.

A technique for sampling a primitive ID map. The technique includes identifying a sample point having a location in a texture space; obtaining a primitive ID sample from the primitive ID map based on the location of the sample point in the texture space; identifying a primitive based on the primitive ID; testing the location in the texture space for inclusion within the identified primitive; and selecting either the primitive ID or a different primitive ID based on the testing.

The invention discloses a special effect rendering method, device and equipment, a medium and a product, and the method comprises the steps: determining an initial directed acyclic graph corresponding to an initial rendering link according to the initial rendering link of a special effect; according to the initial directed acyclic graph, determining at least one reference rendering link and a texture number corresponding to the at least one reference rendering link; wherein the at least one reference rendering link comprises rendering links, corresponding to the initial directed acyclic graph, of various different texture numbers, and the texture number corresponding to the reference rendering link represents the number of minimum texture spaces needing to be occupied in the execution process of the reference rendering link; the target rendering link is determined from the at least one reference rendering link according to the texture number corresponding to the at least one reference rendering link, and the special effect is rendered according to the target rendering link, so that the number of texture spaces allocated to special effect rendering in the memory resources is reduced, and the rendering efficiency is improved. The problem that the occupation amount of special effect rendering on memory resources is too high is solved.

A rendering controller configured to render lights in a three-dimensional (3D) scene is disclosed. The 3D scene includes one or more objects. Each object is associated with a plurality of on-surface reservoirs. The rendering controller is further configured to provide light transport computation in texture space utilizing resampled importance sampling (RIS) or weighted reservoir sampling (WRS) based on the on-surface caches. The rendering controller is configured to compute shading efficiently (i.e., direct, and indirect illumination) of the 3D scene in multi-viewer applications present in the cloud, which involves complex lighting scenarios.

The invention relates to the technical field of image processing, in particular to a plankton image enhancement method based on a deep learning model. The method comprises the following steps: acquiring an original image of plankton to be enhanced; analyzing the original image through a deep learning model, and extracting plankton shell grains and flagellum to form periodic texture space arrangement characteristics and spectral absorption characteristics of a chlorophyll-dominated pigment region; and positioning a texture dense region based on the texture space arrangement features, performing pixel-by-pixel phase alignment calibration on the texture dense region, and optimizing the texture features of the texture dense region through feature superposition to form a texture optimization region. Through the deep learning model and the image processing enhancement technology, accurate optimization of the plankton image texture features and natural restoration of the color attributes are realized, so that the detail identification degree, the color authenticity and the overall integrity of the plankton image are improved.

In order to provide efficient triangle index mapping for object spatial shading, geometric processing comprises: dividing UV coordinate data of an object to be shaded into UV layers such that each UV layer comprises non-overlapping triangles with coordinates in the range of 0 to 1; triangular index (index, ID) information is generated for the UV layer to be used for spatial shading of the object, and ray tracing of triangular IDs is performed for sample points in the UV layer. Based thereon, a unique texture space having non-overlapping triangles in the range of 0 to 1 is provided to store texture space shading. A rendering device for such geometric processing is beneficial to providing an efficient solution to construct an object space shading framework.

The embodiment of the invention provides a scene rendering method and device, equipment and a storage medium. The method comprises the following steps: determining a corresponding visible texel set according to a mapping texel point of each pixel point in a current to-be-rendered frame in a target texture image of a specified rendering scene; the visible texel sets are reported to a server side, so that the server side combines the visible texel sets reported by multiple terminals into a visible texel union set, and the visible texel union set is issued to each terminal through a reference texture image subjected to texture rendering; and according to the reference texture image, rendering the current to-be-rendered frame and then displaying the current to-be-rendered frame. According to the embodiment of the invention, one-time efficient texture rendering and texture rendering multiplexing of multiple terminals in the texture space for the specified rendering scene can be realized, the repeated texture rendering overhead of the multiple terminals for each rendering of the specified rendering scene is greatly reduced, and the rendering frame rate and smooth display of each terminal for the specified rendering scene are improved.

This disclosure provides systems, apparatus, devices, and methods for a tessellation oracle for texture space shading, including computer programs encoded on a storage medium. A processor obtains an indication of a UV parameterization for each geometry unit in a set of geometry units and a target number of pixels for each region of the UV parameterization, wherein the UV parameterization includes a first set of UV coordinates of an object space. The processor renders the set of geometry units to obtain a second set of UV coordinates of the screen space and a set of derivatives of the second set of UV coordinates. The processor calculates a resolution of the mip region map based on the set of derivatives and the number of target pixels for each region. The processor outputs an indication of the calculated resolution.

This disclosure provides systems, devices, apparatuses, and methods, including computer programs encoded on a storage medium, for sampler feedback for texture space shading. The processor may assign each shading element of the set of shading elements associated with the geometry unit to a corresponding group of shading elements of the set of groups of shading elements. The processor may identify whether each coloring element is a visible coloring element. The processor may calculate a group offset value for each of the set of pigmented elements based on a number of visible pigmented elements of the set of pigmented elements. The processor may calculate an element offset value for each colored element based on the number of visible colored elements. The processor may assign a texture memory to the visible colored element based on the element offset value and the set of offset values.

This disclosure provides a method, apparatus, storage medium, and electronic device for adjusting a virtual model. The method includes: acquiring a block to be adjusted, where the block to be adjusted is any one of multiple texture blocks obtained by unfolding the model in texture space; determining the texture identifier of the current master-order point on the master-order edge to obtain a first texture identifier, where the master-order edge is any one of multiple consecutive edges in the block to be adjusted, and the current master-order point is a texture point on the master-order edge; determining a deformation adjustment mode for texture points contained in a second texture set based on the first texture identifier, where the second texture point set consists of texture points in the block to be adjusted excluding the master-order point on the master-order edge; and deforming and adjusting the texture points contained in the second texture set based on the deformation adjustment mode to obtain an adjusted virtual model. This disclosure solves the technical problem in related technologies where some parts of the virtual model are distorted during deformation.

The application discloses a method for improving the visual effect of a 3DMM face model. Existing methods ignore the fidelity of the face model in human visual perception, and the designed model and method do not match the subjective feeling of people. The method of the application first pre-processes and image normalizes a face data set, outputs 3DMM reconstruction coefficients and radiation compensation coefficients through a neural network, decodes a personalized face model through a Basel model, fuses the texture vector of the personalized face model with the radiation compensation coefficients, calculates a loss function, restricts the network learning direction, and optimizes the visual effect of the face model. The radiation intensity compensation module and the texture loss function added in the original method can improve the texture space range of the reconstructed face model. The method can effectively improve the expression deficiency of the 3DMM parameterized face model and improve the visual performance of the model under human visual perception.

Embodiments are disclosed for neural texture mapping. In some embodiments, a method of neural texture mapping includes obtaining a plurality of images of an object, determining volumetric representation of a scene of the object using a first neural network, mapping 3D points of the scene to a 2D texture space using a second neural network, and determining radiance values for each 2D point in the 2D texture space from a plurality of viewpoints using a second neural network to generate a 3D appearance representation of the object.

The invention provides a sampler texture feedback method, a graphics processor, electronic equipment and a storage medium, and relates to the technical field of graphics processing. The method comprises the following steps: receiving and analyzing a sampler feedback instruction through a shader processing module to obtain texture sampling data for feedback processing; and a texture sampling module reuses a texture sampling path based on texture sampling data to execute texture space mapping, generates a texture hierarchy data storage address, and writes a request to update a target cache unit by using a texture address with a feedback flag bit, so that the target cache unit records the use condition of a corresponding texture region and hierarchy. According to the technical scheme, under the condition that independent hardware and high instruction overhead are not increased, the texture access statistics and the texture sampling process can be cooperatively completed on a hardware assembly line, so that the texture feedback data generation efficiency can be improved, the access pressure of a feedback path can be reduced, and the accuracy of the texture level use condition can be enhanced.

Techniques and systems are provided for three-dimensional model segmentation. For instances, a process can include: rendering a three-dimensional (3D) model of an object based on a 3D mesh model and a texture of the object; generating a view of the 3D model based on the rendered 3D model; generating a texture space mask based on the texture of the object using a first machine learning (ML) model; generating a labeled mask based on a second ML model; assigning labels to the texture space mask based on the labeled mask to obtain a labeled texture space mask; and generating a 3D mask based on the labeled texture space mask.

The invention discloses a texture mapping matching detection method and device, equipment and a storage medium. The method comprises the steps that a three-dimensional model and a texture map of an object are acquired, and a texture image area in the texture map is used for determining the display effect of a model area; the three-dimensional model is mapped to a texture space, a texture coordinate graph is obtained, and a texture coordinate area in the texture coordinate graph is obtained by mapping a model area contained in the three-dimensional model; obtaining a region adaptation degree between each texture image region in the texture map and a corresponding texture coordinate region in the texture coordinate graph; and detecting the matching between the texture map and the three-dimensional model based on the obtained region adaptation degree to obtain a matching detection result. According to the invention, processing resources can be saved, and the matching detection efficiency and accuracy of the texture mapping can be improved.

Approaches presented herein can utilize a network that learns to embed three-dimensional (3D) coordinates on a surface of one or more 3D shapes into an aligned two-dimensional (2D) texture space, where corresponding parts of different 3D shapes can be mapped to the same location in a texture image. Alignment can be performed using a texture alignment module that generates a set of basis images for synthesizing textures. A trained network can generate a basis shared by all shape textures, and can predict input-specific coefficients to construct the output texture for each shape as a linear combination of the basis images, then deform the texture to match the pose of the input. Such an approach can ensure alignment of textures, even in situations with at least somewhat limited network capacity. To unwrap shapes of complex structure or topology, a masking network can be utilized that cuts the shape into multiple pieces to reduce the distortion in the 2D mapping.