38 results about "Mesh geometry" patented technology

Ways to post-process a decoded mesh and modify received triangles per patch to improve the mesh geometry are described herein. Since the transmitted geometry contains the high-resolution surface information, the information is able to be applied to the mesh reconstruction operation to generate triangles that are aligned with the original surface. Methods include generating new triangles by splitting the received triangles' edges according to their size, by inserting new vertices at the triangle's centroids, by splitting the vertices, and by performing marching cubes in surfaces defined by the geometry images.

Computer-implemented methods and systems for processing geometry replacements are disclosed. The methods include decoding / encoding a syntax element associated with a coding mode from / into a bitstream associated with geometry displacements; and reconstructing / converting, based on a coefficient configuration associated with the coding mode, a plurality of quantized transform coefficients from / to a plurality of zero-run length codes.

Some implementations relate to methods, systems, and computer-readable media for providing mesh retopology for improved animation of three-dimensional avatar heads. The system receives a three-dimensional mesh that is a representation of an avatar head; defines local coordinate frames relative to geometric features of the mesh; utilizes a machine learning model to predict frame fields based on these features; blends the predicted frame fields to calculate unified directional constraints for each mesh face element; and applies quad meshing techniques to extract a quad mesh representation of the avatar head.

The invention discloses a hexahedral mesh intelligent simplification method with guaranteed analysis precision, and belongs to the technical field of hexahedral mesh simplification, and the method comprises the following steps: 1, carrying out the feature extraction of layers and columns of a hexahedral mesh, including geometric features, topological features, quality features and physical features; step 2, carrying out validity check on the layers and the columns; 3, predicting the deletion probability of a deletable layer / column based on the constructed simplified neural network HSimNet; and step 4, executing layer / column deletion operation. According to the method, physical characteristics of layers and columns are introduced into hexahedral mesh simplification for the first time, model simplification is associated with physical problems, geometric characteristics are introduced into hexahedral mesh simplification, and layer and column structures causing geometric ineffectiveness of the mesh are pre-judged, so that geometric effectiveness of the simplified mesh is guaranteed; topological features and quality features are introduced into hexahedral mesh simplification, so that the overall quality of the simplified mesh is ensured.

The invention relates to a rapid rendering method for an urban Beidou cubic grid. The method comprises the following steps: firstly, acquiring urban low-altitude geographic space data; constructing a multi-level grid system according to conflict detection precision and response requirements by using a Beidou cubic grid subdivision technology, and associating codes and airspace attributes with grid units; unloading the geometric generation task to a GPU for parallel calculation, and generating rendering adaptive grid geometric data; then developing a three-dimensional rapid rendering algorithm to realize real-time rendering of any region and precision grid; subsequently establishing a rendering result and airspace management cooperation mechanism to assist route planning, management and control and zoning; and finally, an algorithm optimization module is linked. The invention aims to solve the problems that the existing ground object 3D rendering adaptive city low-altitude field is insufficient, the conflict detection precision is not matched, the real-time performance is poor and the existing ground object 3D rendering adaptive city low-altitude field is disjointed with a low-altitude management service.

Computer-implemented methods and systems for processing geometry replacements are disclosed. The methods include: packing / unpacking, in a block-boundary-aligned arrangement, a plurality of samples belonging to a plurality of levels of detail (LoD) associated with geometry displacements, into / from a two-dimensional plane including a plurality of blocks.

The invention discloses an end-to-end field optimization surface reconstruction method based on Gaussian sputtering guidance, and belongs to the field of computer vision and computer graphics. Comprising the following steps: 1) Gaussian guidance field optimization: defining an implicit symbol distance field by using a parameterized MLP network, and initializing and optimizing a surface through a microcosmic contour surface extraction method; gaussian units are bound with the extracted surface triangular patches, the positions of the patches are parameterized through the vertexes of the patches, rotation and scaling are carried out, regularization constraints based on the minimum wrapped ellipse and the distribution entropy are introduced, it is ensured that the Gaussian units are accurately attached to the surface and evenly distributed on the surface, and a result obtained through rendering guides field optimization. And 2) local multi-resolution: identifying surface voxels based on the optimized symbol distance field to carry out adaptive octree subdivision so as to realize multi-resolution improvement. And 3) adopting an inner and outer double-layer cyclic training architecture, optimizing the symbolic distance field and the grid geometric parameters on the outer layer, and optimizing a bound Gaussian unit on the inner layer to realize end-to-end joint optimization of surface geometry and Gaussian rendering.

The invention provides an unstructured parallel grid quality optimization method based on grid unit merging. According to the method, when it is detected that a negative volume unit exists in a computational grid, the negative volume unit and an adjacent unit are combined, and optimized grid geometric information, topological information, boundary condition information and butt joint surface information are reconstructed. And through loop iteration until no negative volume unit exists in the optimized grid, the quality of the computational grid is remarkably improved, and the efficiency and precision of CFD numerical simulation are improved. The method can be applied in a multi-block parallel grid environment, supports grid optimization of a large-scale complex geometric model, and is suitable for two-dimensional and three-dimensional unstructured grids.

The present application relates to a kind of three-dimensional geological grid model to numerical analysis model conversion and attribute data mapping method, to improve the data conversion accuracy and efficiency between geological modeling and numerical analysis.The method includes the following steps: first, from the geological modeling software export includes grid geometry information and physical attribute first grid data file;By depth analysis, topological rearrangement and unit type matching and the method for accurately mapping physical attribute data generation second format file in line with the requirement of target software;Finally import second format file in numerical analysis software, automatically generate numerical analysis model has been endowed with initial attribute, complete from geological model to numerical analysis model seamless conversion.The present application is accurately mapped to the attribute data of target grid topological sequence, strictly aligns physical attribute data and geometric data, solves the attribute loss problem caused by topological rearrangement and geometry conversion in traditional method, so as to improve the accuracy and reliability of numerical analysis model.

The application discloses a hexahedral mesh intelligent simplification method with analysis precision ensured, and belongs to the technical field of hexahedral mesh simplification, and comprises the following steps: step one, feature extraction is performed on layers and columns of the hexahedral mesh, including geometric features, topological features, quality features and physical features; step two, effectiveness checking is performed on the layers and columns; step three, based on the constructed simplification neural network HSimNet, the deletion probability of layers / columns that can be deleted is predicted; and step four, layer / column deletion operation is performed. In the application, the physical features of layers and columns are introduced in the hexahedral mesh simplification for the first time, the model simplification is connected with the physical problem, the geometric features are introduced in the hexahedral mesh simplification, the layer and column structures that cause invalid grid geometry are predicted, so that the geometric effectiveness of the simplified grid is ensured; the topological features and the quality features are introduced in the hexahedral mesh simplification, so that the overall quality of the simplified grid is ensured.

An apparatus includes one or more processors, and one or more memories storing instructions that, when executed by the one or more processors, cause the apparatus to: segment, for a frame of three-dimensional object data, a mesh of the three-dimensional object data into one or more patches; determine contours of the one or more patches, wherein the contours of the one or more patches comprise one or more vertices having one or more connected neighboring vertices belonging to another patch, or one or more vertices on a border of the mesh; generate a contour mesh of the three-dimensional object data using the contours of the one or more patches, wherein the contour mesh comprises a plurality of the one or more patches; and encode the contour mesh of the three-dimensional object data into a bitstream using a coding method.

Systems and methods are provided for predictive mesh coding based on a centroid-normal (C-N) representation. An encoder generates C-N representations of a high-resolution (hi-res) mesh and a downscaling of the mesh (lo-res mesh), each representation having respective centroids and normals. The encoder generates predicted centroids corresponding to the hi-res mesh based on the lo-res centroids using a centroid prediction model. The encoder generates predicted normals corresponding to the hi-res mesh based on the predicted centroids and lo-res normals using a normal vector prediction model. Residuals are computed for the respective predicted geometry data. The encoder transmits encodings of the lo-res mesh and the residuals for decoding at a client device.

The application discloses a nearest neighbor query optimization algorithm of GeoHash, and based on inherent geometric characteristics of GeoHash, by mining the inherent correlation between the geometric characteristics of the GeoHash grid and the spherical constraint, a judgment tool optimized specially for the grid level comparison is constructed, and unified processing from the grid to the point level judgment is realized; in view of the difficulty of the nearest neighbor query, a multi-level progressive pruning architecture is innovatively proposed based on the spatial distribution physical characteristics, the accurate calculation complexity is reduced to the minimum through a distance factor pre-computation model, and a complete optimization solution is provided for large-scale spatial data retrieval.

The invention relates to a method for adapting a model of a three-dimensional object (2). A starting model of the object (2) is optimized into the form of a shell model (1) using an optimization process. A base-surface-free rib grid model (5) is extracted from the shell model (1) and is transformed into a rib polygonal model (6). The rib polygonal model (6) is used to adapt the starting model of the object (2) in that the ribs (2.2) of the starting model are replaced with the rib polygonal model (6).

The invention discloses a three-dimensional grid geometric refinement method and system based on texture boundary constraint, a terminal and a medium, and the method comprises the steps: obtaining a three-dimensional grid model, and carrying out the enhancement processing of a texture image of the three-dimensional grid model; extracting linear boundary features from the enhanced texture image to obtain a texture boundary line segment; mapping the texture boundary line segments to the surface of the three-dimensional grid model and taking the texture boundary line segments as texture boundary constraints, and constructing a candidate point set containing the texture boundary constraints in combination with an original geometric structure of the three-dimensional grid model; and generating a refined three-dimensional mesh model through a constrained mesh construction mode, and realizing consistent alignment of geometric units and texture semantic boundaries. According to the method, a network construction mechanism of texture enhancement and boundary constraint is introduced, so that the photogrammetry three-dimensional grid model realizes consistent alignment of geometric units and texture semantic boundaries under the condition of given geometric resolution, and the three-dimensional grid model with more reasonable structural expression and more accurate boundary description is obtained.

This invention belongs to the field of electromagnetic simulation design, specifically a method for HFSS mesh format conversion. Addressing the challenges of complex HFSS proprietary mesh data structures, closed formats, and a lack of public interfaces, this invention proposes a systematic analytical and reconstruction method. This method achieves complete extraction and accurate mapping of mesh topological relationships, material properties, and boundary features. While maintaining the geometric accuracy and topological consistency of the original mesh, it efficiently and accurately converts proprietary format data into standardized, universal mesh format files. This effectively breaks down data barriers between different simulation software, constructing a unified data representation system that can be shared across solution platforms. This provides a unified and reliable mesh data foundation for cross-platform simulation verification, multi-tool result comparison, and multi-physics collaborative analysis.

The generation of the depth image is improved by more efficient encoding using video codecs. The mapping of depth to the luminance channel is performed without using all available bits, and the remaining bits are used to generate a depth scaling factor, which is incorporated into the bilinear interpolation algorithm used during rasterization. A normal filtering procedure is described. In this procedure, the positions of the vertices are adjusted according to the normals estimated from the surface pixels. After decoding the depth image, the pixels related to the surface of a triangle are collected and used to estimate a plane and the normal of the plane. The normal is compared with the normal obtained from the plane defined by the three vertices of the triangle. If there is no match, the position of the vertex is adjusted to match the normal estimated from the surface of the pixel. The adjustment can follow an iterative minimization process.

Depth image generation is improved by more efficient encoding using video codecs. The mapping of the depth to the luma channel is performed by not using all bits available, and with the remaining bits, a depth scaling factor is generated and incorporated into the bilinear interpolation algorithm used during rasterization. A normal filtering procedure is described, where the positions of vertices are adjusted according to the normal estimated from the surface pixels. After decoding the depth image, the pixels related to the surface of a triangle are collected and used to estimate a plane and the normal of the plane. The normal is compared to the normal obtained from the plane defined by the three vertices of the triangle. If there is no match, the positions of the vertices are adjusted to match the estimated normal from the pixels' surfaces. The adjustment can follow an iterative minimization process.

The application provides a three-dimensional mesh generation method based on patch autoregressive compression and an electronic device. The three-dimensional mesh generation method based on patch autoregressive compression comprises the following steps: converting an input three-dimensional shape representation into an ordered triangular patch sequence, wherein each triangular patch is defined by the coordinates of its three vertices; using a shape encoder to encode the input three-dimensional shape representation into a latent representation; using an autoregressive decoder to generate each triangular patch in the ordered triangular patch sequence one by one in sequence, with the latent representation as a condition, thereby generating a three-dimensional mesh. By representing a three-dimensional mesh as an ordered patch sequence and performing autoregressive generation, the modeling granularity is improved from the bottom vertex coordinates to the high-level triangular patch. The model can directly learn and generate the topological structure of the mesh, significantly improving the ability to capture the geometric structure and topological relationship of the mesh, thereby achieving the purpose of improving the generation quality and efficiency.

There is provided an information processing device and method capable of independently controlling granularities of UV coordinates and vertex positions. Meta information including vertex information with a first granularity which indicates coordinates of vertices of a mesh is encoded, a geometry image with a second granularity of the mesh is encoded, a texture image with a third granularity of the mesh is encoded, and encoded data of the meta information, encoded data of the geometry image, and encoded data of the texture image are provided. The present disclosure may be applied to, for example, an information processing device, an electronic device, an information processing method, a program, or the like.

The invention discloses an ocean mode grid boundary relation construction method based on adaptive parallel grid coding, and belongs to the technical field of spatial information. The method comprises the following steps: acquiring a coding document generated based on adaptive parallel grid coding, a geographic position relationship, a U grid geometrical relationship table and a T grid geometrical relationship table; constructing a boundary U grid relation table of the U grid, a boundary T grid relation table of the U grid and a boundary T grid relation table of the T grid; on the basis of the constructed relation table, a boundary U grid relation table of the T grid is derived, and the sequential arrangement of the boundary U grids meets the requirement of ocean mode numerical integration. According to the method, the problem that in the prior art, the boundary coding mapping relation in the U grid and the T grid and the boundary coding mapping relation between the U grid and the T grid cannot be directly output is solved, and redundant expenditure of recalculating boundary information in parallel computing in an ocean mode is eliminated.

A method of operating a computer aided design system model for an article to be designed or manufactured, the method performed on a data processing system; the method includes in a CAD system model capable of representing an article as either algebraic geometry or facet geometry, receiving a mesh geometry representing a surface of the article in 3 dimensions. Constraints to be applied to the mesh geometry are received and the mesh geometry is solved as an exact surface. An updated model of the mesh geometry is stored.

Automatically generating on-demand wiring element optimized meshes for augmented reality (AR) devices is disclosed herein. In one example, a computer system comprises processing circuitry configured to obtain a structured file corresponding to a wiring element of a non-virtual device, wherein the structured file comprises wiring element metadata that comprises a first connector terminal descriptor, a second connector terminal descriptor, and a segment descriptor; the segment descriptor corresponds to a plurality of point descriptors; each point descriptor of the plurality of point descriptors comprises a location coordinate; and the structured file omits mesh geometry data for the wiring element. The processing circuitry further generates a three-dimensional (3D) mesh for the wiring element based on the structured file, receive visual imagery data of the non-virtual device, and display a rendering of the 3D mesh overlaid on the visual imagery data of the non-virtual device.

This document describes a method for post-processing the decoded mesh and modifying the triangles received per patch to improve the geometry of the mesh. Since the transmitted geometry contains high-resolution surface information, it can be applied to a mesh reconstruction operation to generate triangles aligned with the original surface. The method includes splitting the edges of the received triangles according to size, inserting new vertices at the triangle centroids, splitting the vertices, and generating new triangles by performing marching cubes within the surface defined by the geometry image.

The application discloses a training method, a simulation method, equipment and a medium of a simulation model of combustion fracturing crack propagation. The training method of the simulation model of combustion fracturing crack propagation based on a graph neural network comprises the following steps: obtaining combustion fracturing crack propagation simulation parameters; generating a triangular mesh geometric model according to the geometric model parameters; performing numerical simulation of combustion fracturing crack propagation according to the generated triangular mesh geometric model and the combustion fracturing engineering parameters to obtain displacement data and crack state data of the triangular mesh geometric model at multiple time steps; constructing a graph structure and determining features according to the displacement data and the crack state data of the triangular mesh geometric model at the multiple time steps; taking graph data of the graph structure as a training data set according to the constructed graph structure; and training a first graph neural network model constructed in advance according to the training data set.

The invention discloses an engineering component section identification method based on rotation optimization and Chamfer distance, belongs to the field of building information models and intelligent construction, and can solve the problems that semantic information of a component is lost and the section type is difficult to identify after a BIM / CAD model is converted into a general three-dimensional grid format. And a high-fidelity geometric model with standard section attributes is provided for a simulation pre-processing engine. The method does not depend on parameterization information of an original model, is only based on three-dimensional grid geometric data, and realizes high-precision and high-robustness identification and standardized matching of typical component section types such as beams, columns, supports and the like through extension direction analysis and based on continuous optimization matching of differential transformation and Chamfer distance.

Systems and methods are provided for predictive mesh coding based on a centroid-normal (C-N) representation. An encoder generates C-N representations of a high-resolution (hi-res) mesh and a downscaling of the mesh (lo-res mesh), each representation having respective centroids and normals. The encoder generates predicted centroids corresponding to the hi-res mesh based on the lo-res centroids using a centroid prediction model. The encoder generates predicted normals corresponding to the hi-res mesh based on the predicted centroids and lo-res normals using a normal vector prediction model. Residuals are computed for the respective predicted geometry data. The encoder transmits encodings of the lo-res mesh and the residuals for decoding at a client device.

According to one aspect of the present disclosure, a method of decoding is provided. The method may include decoding a first syntax element to determine a first QP value associated with a first hierarchical subdivision level of a base mesh. In response to the delta QP signaling being allowed for a second hierarchical subdivision level, the method may include decoding a third syntax element to determine a first delta QP value for the second hierarchical subdivision level. The method may include determining a second QP value for the second hierarchical subdivision level based on the first QP value and the first delta QP value. The method may include determining first and second sets of displacement wavelet coefficients based on the first QP value and the second QP value, respectively. The method may include decoding the base mesh based on the first and second sets of displacement wavelet coefficients.

The application provides a panoramic image dual perception enhancement method and device fusing deformable convolution and spherical attention. The method comprises: mapping an ERP image into a polyhedral mesh vertex, inputting image features of all mesh vertices into a U-shaped coding and decoding network to obtain an image perception result; the U-shaped coding and decoding network comprises a D-level encoder and a D-level decoder, each level of the encoder comprises M stacked dual perception enhancement modules and a down-sampling layer, each level of the decoder comprises M stacked dual perception enhancement modules and an up-sampling layer, the encoder and the decoder are connected through a jump connection to transmit features between corresponding levels, and the dual perception enhancement module comprises a deformable spherical convolution branch, a deformable spherical local self-attention branch and an adaptive gating fusion block. Based on the dual perception enhancement module, the application can realize deep collaboration of spherical discrete mesh geometry adaptive capability and global semantic modeling capability, and improve the perception performance of the ERP image.

A decal application program applies textures to three-dimensional models through use of a proxy mesh. The decal application program accesses the three-dimensional model source material data which describes surface appearances values associated with the three-dimensional model. The decal application program also accesses decal source material data which describes one or more surface appearance values associated with a decal object. The decal application program generates a proxy mesh for a portion of a surface of the three-dimensional model data, with proxy mesh geometric data representing a portion of the surface of the three-dimensional model. The decal application program deforms the proxy mesh to minimize distance values between the proxy mesh geometric data and a portion of three-dimensional model source material data that represents the portion of the surface of the three-dimensional model. The decal application program then applies the decal data onto the deformed proxy mesh.