CN116310151A - Vector model conversion method, system, device and medium based on digital twin - Google Patents

Vector model conversion method, system, device and medium based on digital twin Download PDF

Info

Publication number
CN116310151A
CN116310151A CN202310586437.7A CN202310586437A CN116310151A CN 116310151 A CN116310151 A CN 116310151A CN 202310586437 A CN202310586437 A CN 202310586437A CN 116310151 A CN116310151 A CN 116310151A
Authority
CN
China
Prior art keywords
model
vector
scalar
points
vector model
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202310586437.7A
Other languages
Chinese (zh)
Other versions
CN116310151B (en
Inventor
李腾
崔翔
赵元汉
赵影
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shandong Jierui Information Technology Industry Research Institute Co ltd
Shandong Jerei Digital Technology Co Ltd
Original Assignee
Shandong Jierui Information Technology Industry Research Institute Co ltd
Shandong Jerei Digital Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shandong Jierui Information Technology Industry Research Institute Co ltd, Shandong Jerei Digital Technology Co Ltd filed Critical Shandong Jierui Information Technology Industry Research Institute Co ltd
Priority to CN202310586437.7A priority Critical patent/CN116310151B/en
Publication of CN116310151A publication Critical patent/CN116310151A/en
Application granted granted Critical
Publication of CN116310151B publication Critical patent/CN116310151B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Computer Graphics (AREA)
  • Geometry (AREA)
  • Software Systems (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Complex Calculations (AREA)
  • Processing Or Creating Images (AREA)

Abstract

The invention discloses a vector model conversion method, system, device and medium based on digital twin, and belongs to the technical field of three-dimensional modeling. The method is characterized by comprising the following steps: importing the vector model into a three-dimensional engine; the system performs the following vector scalar processing procedure on the vector model based on the set subdivision threshold: obtaining the point, line, surface and topological relation of a vector model by reading the file information of the vector model, and determining the basic shape of the vector model; constructing a scalar model corresponding to the vector model based on the basic shape of the vector model and the topological relation among the vector models; checking and correcting the constructed scalar model; and carrying out subdivision calculation on the corrected integral model, and outputting scalar models with different subdivision degrees. Compared with the traditional manual mould turning, the invention has the advantages of time and labor saving, reduced consumption of manpower resources, reduced production cost and improved modeling efficiency.

Description

Vector model conversion method, system, device and medium based on digital twin
Technical Field
The invention relates to a vector model conversion method, system, device and medium based on digital twin, belonging to the technical field of three-dimensional model creation.
Background
The application of the digital twin technology firstly establishes various digital twin models for physical objects, fully utilizes the models and data to transfer real data of the operation of the physical objects acquired by the Internet of things and the sensors to the twin models, and realizes the visualization, fault diagnosis, prediction, performance optimization and the like of the physical objects by means of the technologies such as augmented reality, mixed reality technology, artificial intelligence and the like through the presentation, simulation, analysis and optimization of the digital twin models.
The model is used as a mapping carrier in the digital twin technology, and has the biggest characteristic of fusing the real-time data of the human-computer object ternary space full life cycle with continuous iterative optimization. Besides the physical entity characteristics reflected by the characterization data obtained by the accurate mapping of the things-to-things sensing, the digital twin model also accurately maps the behavior rules and mutual feedback mechanisms of the digital twin model, and particularly the characterization data which can be obtained by the sensing means limitation in many times is incomplete, not fine enough, not accurate enough and not timely enough, and only the model knowledge is relied on to infer.
In practical projects, various difficulties are usually encountered in model construction, and errors exist in both a traditional three-dimensional modeling mode and an existing scanning modeling mode, so that physical movements of the real world cannot be truly reflected. The most accurate way is to construct a twin model by using the industrial digital model of the real equipment. Generally, the digital model basically belongs to a vector model, and because the current mainstream three-dimensional engine is presented and researched and developed by a scalar model, the vector conversion is not processed more carefully by the three-dimensional engine, so that messy points and lines can be generated when the vector model is directly led into the three-dimensional engine, a standard triangular model can not be generated, and the model can not be directly used for program development of the three-dimensional engine.
In view of the above, there is a need for a method of converting a vector model into a scalar model.
Disclosure of Invention
In order to solve the problems, the invention discloses a vector model conversion method, a vector model conversion system, a vector model conversion device and a vector model conversion medium based on digital twinning, which are used for solving the problems of multiple surfaces, multiple points, messy lines and the like caused by vector model processing of a three-dimensional engine, realizing scalar processing of the vector model by the three-dimensional engine and creating scalar models with different precision through the vector model.
The technical scheme adopted for solving the technical problems is as follows:
in a first aspect, the present invention provides a vector model transformation method based on digital twinning, comprising the steps of:
s1: importing the vector model into a three-dimensional engine;
s2, the system executes the following vector conversion amount processing procedure on the vector model based on the set subdivision threshold value:
s21, obtaining point, line, surface and topological relation of a vector model by reading file information of the vector model, and determining the basic shape of the vector model;
s22, constructing a scalar model corresponding to the vector model based on the basic shape of the vector model and the topological relation among the vector models in S21;
s23, checking and correcting the scalar model constructed in the S22;
s24, carrying out subdivision calculation on the corrected integral model, and outputting scalar models with different subdivision degrees.
Further, the specific step of S21 includes:
obtaining the expression mode and rule of the geometric model forming the vector model in the vector model file in the machine language through decompilation technology;
the topological relations among points, vectors and vectors of the vector model are obtained by adopting a quadtree depth traversal principle, the relations such as intersection, contact, overlapping and the like among the points and the vectors of the vector model are obtained by vector calculation, and the basic shape of the vector model is determined by expressing the relations;
based on the edge points and the inclusion points between the vector models, the topological relation between the vector models is obtained.
Further, the specific step of S22 includes:
scalar operation is carried out on the vector and the point as well as the vector and the vector of each vector model, and the distance between the vector and the point and the distance between the vector and the vector of each vector model are obtained;
generating points, lines and planes of a scalar model based on information of points in each vector model and distances among vectors in each vector model and points, vectors and vectors, and constructing the scalar model based on the points, lines and planes of the scalar model; the representation rule of the points, lines and planes in the three-dimensional scene is as follows: points are defined as βv (x, y, z), line segments as βl (V1, V2), faces as βs (V1, V2, V3);
based on the subdivision threshold, points are added on line segments of each scalar model, and the added points are connected with other points of the surface where the points are located, so that the surface after connection is still a triangular surface.
Further, the specific step S23 includes:
and (3) further correcting the scalar model constructed in the step S22 by adopting a binary tree preamble traversal principle: randomly acquiring a point of the scalar model, performing topological relation conversion and verification, continuously performing point removal and replacement, removing redundant points or surfaces, and correcting the model to normalize the model;
further correcting the position relation among scalar models and adding a plurality of topological relation information which can be identified by scalar three-dimensional modeling software among the models: the angular and positional relationships between the different faces of the model and between the models are calculated by the normal line of each face of the scalar model and appended to the scalar model to further correct the connection or positional relationship between the scalar models that can be identified by the scalar three-dimensional modeling software.
Further, the specific step of S24 includes:
reserving points on adjacent surfaces among scalar models;
comparing the connecting line distance between the internal points of the scalar model with a preset subdivision threshold value, wherein the connecting line distance between the two points is larger than the subdivision threshold value, and reserving the two points; the distance between two points is smaller than the subdivision threshold, one point is removed, the other point is reserved, and the reserved point is reconnected with the other points.
In a second aspect, the present invention provides a digital twinning-based vector model conversion system, the system comprising:
the model importing module is used for importing the vector model into the three-dimensional engine;
the method execution module is used for executing a vector conversion amount processing process on the vector model;
wherein, the method execution module further comprises:
the analysis unit is used for obtaining the point, line, surface and topological relation of the vector model by reading the file information of the vector model and determining the basic shape of the vector model;
a model construction unit, configured to construct a scalar model corresponding to the vector model based on the basic shape of the vector model and the topological relation between the vector models;
the model correction unit is used for checking and correcting the scalar model;
the model output unit is used for carrying out subdivision calculation on the corrected integral model and outputting scalar models with different subdivision degrees.
In a third aspect, the present invention provides a vector model conversion device based on digital twinning, the device comprising:
a memory for storing a computer program;
a processor for implementing the steps of the digital twinning based vector model conversion method described above when executing the computer program.
In a fourth aspect, the present invention also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the digital twinning based vector model conversion method as described above.
The beneficial effects of the invention are as follows:
compared with the operation of converting a conventional three-dimensional engine vector model into a scalar model, the conversion method provided by the invention is more standardized and more applicable, and meanwhile, the model is lighter and has no redundant dotted line and surface; compared with the conversion software on the market, the method is simpler and lighter, is not bulkier, and increases the utilization rate of the CPU and the GPU, so that the conversion rate is more efficient; compared with the traditional manual mould turning, the mould turning machine is more time-saving and labor-saving, reduces the consumption of human resources, reduces the production cost and improves the productivity.
Drawings
FIG. 1 is a flow chart of a digital twinning-based vector model transformation method according to the first embodiment;
FIG. 2 is a diagram of a digital twinning-based vector model conversion system according to the second embodiment;
fig. 3 is a diagram showing a construction of a vector model conversion device based on digital twin in the third embodiment.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
in order to clearly illustrate the technical features of the present invention, the present invention will be described in detail below with reference to the following detailed description and the accompanying drawings. The following disclosure provides many different embodiments for implementing different configurations of the invention. In order to simplify the present disclosure, components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and processes are omitted so as to not unnecessarily obscure the present invention.
In this embodiment, a digital twin model of a stool (a default stool is formed by a plurality of cuboids) is taken as an example, and the digital twin-based vector model conversion method of the present invention is described in detail.
Example 1
A vector model conversion method based on digital twin is shown in figure 1, and specifically comprises the following steps:
s1, importing a vector model of a stool into a three-dimensional engine;
s2, setting a subdivision threshold value to be 3nm, and executing a vector transformation amount processing method on the vector model of the stool after the system responds;
the processing method comprises the following steps:
s21, obtaining points, lines, surfaces and topological relations of a stool vector model by reading model file information of the stool, and determining the basic shape of the stool; the method specifically comprises the following steps:
obtaining the expression modes and rules of a plurality of cuboid vector models forming a stool in a vector model file in a machine language through decompilation technology;
obtaining topological relations among points, vectors and vectors of the stool vector model by adopting a quadtree depth traversal principle, obtaining relations such as intersection, contact, overlapping and the like between the points and the vectors of the vector model by vector calculation, and determining the basic shape of the stool by expressing the relations;
based on edge points and inclusion points among the cuboid vector models, a child-parent topological relation among a plurality of cuboid vector models forming a stool is obtained.
S22, constructing a scalar model corresponding to the vector model based on the basic shape of the vector model and the sub-parent topological relation among the cuboid vector models in S21; the method specifically comprises the following steps:
scalar operation is carried out on the vector and the point and the vector of each cuboid vector model, and the distances between the vector and the point and between the vector and the vector of each cuboid vector model are obtained;
generating points, lines and planes of a scalar model based on information of points in each cuboid vector model and distances between middle vectors and points, vectors and vectors of each cuboid vector model, and constructing the scalar model based on the points, lines and planes of the scalar model; the representation rule of the points, lines and planes in the three-dimensional scene is as follows: points are defined as βv (x, y, z), line segments as βl (V1, V2), faces as βs (V1, V2, V3);
based on the set subdivision threshold, adding points on the line segments of each cuboid scalar model, and connecting the added points with other points of the surface of the cuboid scalar model to ensure that the surface after connection is still a triangular surface.
S23, checking and correcting the scalar model constructed in the S22; the method specifically comprises the following steps:
and (3) further correcting the stool model constructed in the step S22 by adopting a binary tree preamble traversal principle: randomly acquiring a point of a scalar model, converting and verifying topological relations among the cuboids, continuously moving out and replacing the point in each cuboid, removing redundant points or surfaces, and correcting the model to normalize the model;
further correcting the position relation among the cuboid scalar models and adding a plurality of topological relation information which can be identified by scalar three-dimensional modeling software among the models: the angular and positional relationships between the different faces of the model and between the models are calculated by the normal line of each face of the scalar model and appended to the scalar model to further correct the connection or positional relationship between the scalar models that can be identified by the scalar three-dimensional modeling software.
S24, carrying out subdivision calculation on the corrected integral model, and outputting scalar models with different subdivision degrees; the method specifically comprises the following steps:
reserving points on adjacent surfaces among the cuboid scalar models;
comparing the connecting line distance between the internal points of the scalar model with a preset subdivision threshold value of 3nm, wherein the connecting line distance between the two points is more than 3nm, and reserving the two points; and removing one point, reserving the other point and reconnecting the reserved point with the other point, wherein the connecting distance between the two points is smaller than 3 nm.
Example two
Based on the angle of the functional module, the embodiment provides a vector model conversion system based on digital twin, as shown in fig. 2, including:
the model importing module is used for importing the vector model into the three-dimensional engine;
the method execution module is used for executing a vector conversion amount processing process on the vector model;
wherein, the method execution module further comprises:
the analysis unit is used for obtaining the point, line, surface and topological relation of the vector model by reading the file information of the vector model and determining the basic shape of the vector model;
a model construction unit, configured to construct a scalar model corresponding to the vector model based on the basic shape of the vector model and the topological relation between the vector models;
the model correction unit is used for checking and correcting the scalar model;
the model output unit is used for carrying out subdivision calculation on the corrected integral model and outputting scalar models with different subdivision degrees.
Example III
Based on the hardware perspective, the present embodiment provides a digital twin-based vector model conversion device, whose structure is shown in fig. 3, including a processor, a memory and a bus, where the memory stores a computer program, and when the computer device is running, the processor communicates with the memory through the bus, and the processor executes the computer program to perform the steps of the digital twin-based vector model conversion method as described above.
In particular, the above memory and processor can be general-purpose memory and processor, and are not limited herein, and when the processor runs a computer program stored in the memory, the steps of the above vector model conversion method based on digital twin can be performed.
It will be appreciated by those skilled in the art that the structure of the computer device shown in fig. 3 is not limiting of the computer device and may include more or fewer components than shown, or may combine certain components, or split certain components, or a different arrangement of components.
In some embodiments, the computer device may further include a touch screen operable to display a graphical user interface (e.g., a launch interface of an application) and to receive user operations with respect to the graphical user interface (e.g., launch operations with respect to the application). A particular touch screen may include a display panel and a touch panel. The display panel may be configured in the form of an LCD (LiquidCrystal Display), an OLED (Organic Light-Emitting Diode), or the like. The touch panel may collect touch or non-touch operations on or near the user and generate preset operation instructions, for example, operations of the user on or near the touch panel using any suitable object or accessory such as a finger, a stylus, or the like. In addition, the touch panel may include two parts, a touch detection device and a touch controller. The touch detection device detects the touch azimuth and the touch gesture of a user, detects signals brought by touch operation and transmits the signals to the touch controller; the touch controller receives touch information from the touch detection device, converts the touch information into information which can be processed by the processor, sends the information to the processor, and can receive and execute commands sent by the processor. In addition, the touch panel may be implemented by various types such as resistive, capacitive, infrared, and surface acoustic wave, or may be implemented by any technology developed in the future. Further, the touch panel may overlay the display panel, and a user may operate on or near the touch panel overlaid on the display panel according to a graphical user interface displayed by the display panel, and upon detection of an operation thereon or thereabout, the touch panel is transferred to the processor to determine a user input, and the processor then provides a corresponding visual output on the display panel in response to the user input. In addition, the touch panel and the display panel may be implemented as two independent components or may be integrated.
Example IV
The embodiment of the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the steps of the vector model conversion method based on digital twinning when being executed by a processor.
It will be appreciated that the methods of the above embodiments, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored on a computer readable storage medium. With such understanding, the technical solution of the present application, or a part contributing to the prior art or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium, performing all or part of the steps of the method described in the various embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only memory (ROM), a random access memory (RandomAccessMemory, RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.

Claims (8)

1. The vector model conversion method based on digital twin is characterized by comprising the following steps of:
s1: importing the vector model into a three-dimensional engine;
s2, the system executes the following vector conversion amount processing procedure on the vector model based on the set subdivision threshold value:
s21, obtaining point, line, surface and topological relation of a vector model by reading file information of the vector model, and determining the basic shape of the vector model;
s22, constructing a scalar model corresponding to the vector model based on the basic shape of the vector model and the topological relation among the vector models in S21;
s23, checking and correcting the scalar model constructed in the S22;
s24, carrying out subdivision calculation on the corrected integral model, and outputting scalar models with different subdivision degrees.
2. The method for converting a vector model based on digital twinning according to claim 1, wherein the specific step of S21 includes:
obtaining the expression mode and rule of the geometric model forming the vector model in the vector model file in the machine language through decompilation technology;
the topological relations among points, vectors and vectors of the vector model are obtained by adopting a quadtree depth traversal principle, the relations such as intersection, contact, overlapping and the like among the points and the vectors of the vector model are obtained by vector calculation, and the basic shape of the vector model is determined by expressing the relations;
based on the edge points and the inclusion points between the basic shapes of the vector models, the topological relation between the vector models is obtained.
3. The method for converting a vector model based on digital twinning according to claim 1, wherein the specific step of S22 includes:
scalar operation is carried out on the vector and the point and the vector of each vector model, and the distances between the vector and the point and between the vector and the vector of the vector model are obtained;
generating points, lines and planes of a scalar model based on information of points in each vector model and distances among vectors in each vector model and points, vectors and vectors, and constructing the scalar model based on the points, lines and planes of the scalar model; the representation rule of the points, lines and planes in the three-dimensional scene is as follows: points are defined as βv (x, y, z), line segments as βl (V1, V2), faces as βs (V1, V2, V3);
based on the subdivision threshold, points are added on line segments of each scalar model, and the added points are connected with other points of the surface where the points are located, so that the surface after connection is still a triangular surface.
4. The method for converting a vector model based on digital twinning according to claim 1, wherein the specific step of S23 includes:
and (3) further correcting the scalar model constructed in the step S22 by adopting a binary tree preamble traversal principle: randomly acquiring a point of the scalar model, performing topological relation conversion and verification, continuously performing point removal and replacement, removing redundant points or surfaces, and correcting the model to normalize the model;
further correcting the position relation among scalar models and adding a plurality of topological relation information which can be identified by scalar three-dimensional modeling software among the models: the angular and positional relationships between the different faces of the model and between the models are calculated by the normal line of each face of the scalar model and appended to the scalar model to further correct the connection or positional relationship between the scalar models that can be identified by the scalar three-dimensional modeling software.
5. The method for converting a vector model based on digital twinning according to claim 1, wherein the specific step of S24 includes:
reserving points on adjacent surfaces among scalar models;
comparing the connecting line distance between the internal points of the scalar model with a preset subdivision threshold value, wherein the connecting line distance between the two points is larger than the subdivision threshold value, and reserving the two points; the distance between two points is smaller than the subdivision threshold, one point is removed, the other point is reserved, and the reserved point is reconnected with the other points.
6. A digital twinning-based vector model conversion system, comprising:
the model importing module is used for importing the vector model into the three-dimensional engine;
the method execution module is used for executing a vector conversion amount processing process on the vector model;
wherein, the method execution module further comprises:
the analysis unit is used for obtaining the point, line, surface and topological relation of the vector model by reading the file information of the vector model and determining the basic shape of the vector model;
a model construction unit, configured to construct a scalar model corresponding to the vector model based on the basic shape of the vector model and the topological relation between the vector models;
the model correction unit is used for checking and correcting the scalar model;
the model output unit is used for carrying out subdivision calculation on the corrected integral model and outputting scalar models with different subdivision degrees.
7. A vector model conversion device based on digital twinning, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the digital twin based vector model conversion method according to any of claims 1 to 5 when executing said computer program.
8. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the digital twinning based vector model conversion method according to any of claims 1 to 5.
CN202310586437.7A 2023-05-24 2023-05-24 Vector model conversion method, system, device and medium based on digital twin Active CN116310151B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310586437.7A CN116310151B (en) 2023-05-24 2023-05-24 Vector model conversion method, system, device and medium based on digital twin

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310586437.7A CN116310151B (en) 2023-05-24 2023-05-24 Vector model conversion method, system, device and medium based on digital twin

Publications (2)

Publication Number Publication Date
CN116310151A true CN116310151A (en) 2023-06-23
CN116310151B CN116310151B (en) 2023-08-08

Family

ID=86785446

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310586437.7A Active CN116310151B (en) 2023-05-24 2023-05-24 Vector model conversion method, system, device and medium based on digital twin

Country Status (1)

Country Link
CN (1) CN116310151B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117182930A (en) * 2023-11-07 2023-12-08 山东捷瑞数字科技股份有限公司 Four-axis mechanical arm binding method, system, equipment and medium based on digital twin

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050232511A1 (en) * 2002-08-09 2005-10-20 Djemel Ziou Image model based on n-pixels and defined in algebraic topology, and applications thereof
CN101119485A (en) * 2007-08-06 2008-02-06 北京航空航天大学 Characteristic reservation based three-dimensional model progressive transmission method
CN115471634A (en) * 2022-10-28 2022-12-13 吉奥时空信息技术股份有限公司 Modeling method and device for urban green plant twins
CN116152444A (en) * 2023-04-04 2023-05-23 山东捷瑞信息技术产业研究院有限公司 Automatic adsorption method, device and medium for three-dimensional scene model based on digital twin

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050232511A1 (en) * 2002-08-09 2005-10-20 Djemel Ziou Image model based on n-pixels and defined in algebraic topology, and applications thereof
CN101119485A (en) * 2007-08-06 2008-02-06 北京航空航天大学 Characteristic reservation based three-dimensional model progressive transmission method
CN115471634A (en) * 2022-10-28 2022-12-13 吉奥时空信息技术股份有限公司 Modeling method and device for urban green plant twins
CN116152444A (en) * 2023-04-04 2023-05-23 山东捷瑞信息技术产业研究院有限公司 Automatic adsorption method, device and medium for three-dimensional scene model based on digital twin

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
肖刚;冶平;张星辰;刘骏;贡克;: "多源异构图像融合跟踪研究现状与展望", 指挥控制与仿真, no. 02 *
马秋禾, 肖蓉, 赵金萍: "基于数据挖掘和知识发现的矢量一体化全局模型", 测绘学院学报, no. 02 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117182930A (en) * 2023-11-07 2023-12-08 山东捷瑞数字科技股份有限公司 Four-axis mechanical arm binding method, system, equipment and medium based on digital twin
CN117182930B (en) * 2023-11-07 2024-02-13 山东捷瑞数字科技股份有限公司 Four-axis mechanical arm binding method, system, equipment and medium based on digital twin

Also Published As

Publication number Publication date
CN116310151B (en) 2023-08-08

Similar Documents

Publication Publication Date Title
EP4120199A1 (en) Image rendering method and apparatus, and electronic device and storage medium
Bracci et al. HexaLab. net: An online viewer for hexahedral meshes
JP6196032B2 (en) Generation of surfaces from multiple 3D curves
JP7343963B2 (en) Dataset for learning functions that take images as input
CN116310151B (en) Vector model conversion method, system, device and medium based on digital twin
Bojsen-Hansen et al. Tracking surfaces with evolving topology.
CN108073682A (en) Based on parameter view functional query database
KR102352942B1 (en) Method and device for annotating object boundary information
JP2022036918A (en) Uv mapping on 3d object with the use of artificial intelligence
CN112927328A (en) Expression migration method and device, electronic equipment and storage medium
Li et al. On surface reconstruction: A priority driven approach
WO2021120834A1 (en) Biometrics-based gesture recognition method and apparatus, computer device, and medium
Li et al. [Retracted] Deep‐Learning‐Based 3D Reconstruction: A Review and Applications
Du et al. Learning Part Generation and Assembly for Sketching Man‐Made Objects
EP4275173B1 (en) Computer-implemented reconstruction of interior rooms
A. Vasilakis et al. Pose partitioning for multi‐resolution segmentation of arbitrary mesh animations
WO2018137454A1 (en) Method of adjusting object shape, and adjustment device
WO2023174561A1 (en) Generating synthetic interior room scene data for training ai-based modules
CN114092653A (en) Method, device and equipment for reconstructing 3D image based on 2D image and storage medium
JP7167990B2 (en) Method, device, system and program for controlling robot, and storage medium
CN107103642B (en) Three-dimensional model voxelization entity filling method
Zhang et al. MeshLink: a surface structured mesh generation framework to facilitate automated data linkage
CN113255530B (en) Attention-based multichannel data fusion network architecture and data processing method
EP4275178B1 (en) Computer-implemented augmentation of interior room models
WO2023179091A1 (en) Three-dimensional model rendering method and apparatus, and device, storage medium and program product

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant