CN112991547A - Model simplification processing method and device, electronic equipment and medium - Google Patents

Model simplification processing method and device, electronic equipment and medium Download PDF

Info

Publication number
CN112991547A
CN112991547A CN202110063539.1A CN202110063539A CN112991547A CN 112991547 A CN112991547 A CN 112991547A CN 202110063539 A CN202110063539 A CN 202110063539A CN 112991547 A CN112991547 A CN 112991547A
Authority
CN
China
Prior art keywords
plane
dimensional model
polyhedrons
original
polyhedron
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
CN202110063539.1A
Other languages
Chinese (zh)
Other versions
CN112991547B (en
Inventor
方昊
潘慈辉
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.)
Seashell Housing Beijing Technology Co Ltd
Original Assignee
Beijing Fangjianghu 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 Beijing Fangjianghu Technology Co Ltd filed Critical Beijing Fangjianghu Technology Co Ltd
Priority to CN202110063539.1A priority Critical patent/CN112991547B/en
Publication of CN112991547A publication Critical patent/CN112991547A/en
Application granted granted Critical
Publication of CN112991547B publication Critical patent/CN112991547B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/12—Edge-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/187—Segmentation; Edge detection involving region growing; involving region merging; involving connected component labelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10028—Range image; Depth image; 3D point clouds

Abstract

The present disclosure provides a model simplification processing method, device, electronic device and storage medium, and relates to the technical field of computers, wherein the method comprises: performing segmentation processing on a three-dimensional space based on a plane in the original three-dimensional model to obtain a polyhedron; constructing an energy equation according to the edge polyhedrons and the common plane information between the adjacent polyhedrons; solving an energy equation, acquiring labels corresponding to all polyhedrons and used for representing whether the polyhedrons are located inside the object, and generating a simplified three-dimensional model based on the labels; the method, the device, the electronic equipment and the storage medium can keep structural characteristics in the original three-dimensional model, and reduce the complexity of the model while ensuring no loss of precision; the calculation complexity is low and the efficiency is high; the real-time performance of three-dimensional model transmission and browsing is improved, and the customer experience is effectively improved.

Description

Model simplification processing method and device, electronic equipment and medium
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a model simplification processing method and apparatus, an electronic device, and a storage medium.
Background
With the improvement of data acquisition level and the development of three-dimensional modeling technology, a three-dimensional model of a large indoor scene can be constructed. How to display the obtained three-dimensional model of the indoor scene on a computer is a key problem of whether the VR technology can be put into use. In the field of computer graphics, the indexes for measuring the quality of a three-dimensional model are as follows: (1) the accuracy of the model; (2) the complexity of the model. The precision of the model is measured by whether the geometric distance between the three-dimensional model and the actual three-dimensional scene is small enough and whether the three-dimensional model can keep the detail part of the actual scene. The complexity of a model generally refers to the number of triangular patches corresponding to a three-dimensional model. At present, when a three-dimensional model of an indoor scene is rendered in real time, the three-dimensional model generally needs to be simplified, so that the model accuracy is maintained and the complexity of the model is greatly reduced. However, the accuracy of the model is reduced by the conventional model simplification method, and therefore, a technical scheme for simplifying the indoor scene model is required.
Disclosure of Invention
The present disclosure is proposed to solve the above technical problems. The embodiment of the disclosure provides a model simplification processing method and device, electronic equipment and a storage medium.
According to a first aspect of the embodiments of the present disclosure, there is provided a model simplification processing method, including: processing an original three-dimensional model based on a preset plane detection strategy to obtain a first plane in the original three-dimensional model; carrying out segmentation processing on a three-dimensional space corresponding to the original three-dimensional model according to the first plane to obtain a geometric element set; wherein the geometric elements include: a polyhedron; constructing an energy equation according to edge polyhedrons located at the edges of the three-dimensional space and common plane information between adjacent polyhedrons; solving the energy equation by using a preset image segmentation algorithm to obtain labels corresponding to all polyhedrons; wherein the label is used for representing whether the polyhedron is positioned in the interior of the object; determining at least one first plane belonging to the surface of the object based on the label, and determining a second plane corresponding to the surface of the object according to the at least one first plane; and generating a simplified three-dimensional model corresponding to the original three-dimensional model according to the second plane.
Optionally, the processing the original three-dimensional model based on a preset plane detection strategy, and obtaining a first plane in the original three-dimensional model includes: carrying out plane detection processing on the original three-dimensional model based on a preset plane detection algorithm to obtain a plurality of plane areas in the original three-dimensional model; and determining the boundaries of the plane areas based on a preset boundary determination algorithm to obtain a plurality of first planes.
Optionally, the plane detection method includes: RANSAC, region growing algorithm; the boundary determination algorithm includes: alpha-shape algorithm.
Optionally, the performing, according to the first plane, a segmentation process on a three-dimensional space corresponding to the original three-dimensional model to obtain a set of geometric elements includes: and extending each first plane in the three-dimensional space so that the first plane divides the space passing through.
Optionally, the determining, based on the tag, at least one first plane belonging to a surface of an object comprises: acquiring a first label and a second label corresponding to two adjacent polyhedrons; acquiring a first plane corresponding to a common plane between two adjacent polyhedrons; determining that this first plane belongs to the object surface if the first label and the second label are different.
Optionally, the determining a second plane corresponding to the object surface based on the at least one first plane comprises: acquiring one or more first planes belonging to the surface of an object; generating the second plane based on the one or more first planes.
Optionally, the constructing an energy equation according to edge polyhedrons located at the edge of the three-dimensional space and common plane information between adjacent polyhedrons includes: acquiring connecting line segments between the centers of the polyhedrons and the centers of a plurality of edge polyhedrons respectively; determining the intersection times of each connecting line segment and the intersection times of the composition surfaces of other polyhedrons; calculating the quotient of the number of the connecting line segments with the odd number of intersection times and the total number of the connecting line segments as the surface probability corresponding to the polyhedron; wherein the surface probability is used to characterize whether the polyhedron has an object surface; generating a first term of the energy equation according to the volume of the polyhedron and the corresponding surface probability; acquiring a first area of a common plane between adjacent polyhedrons; acquiring a second area of the first plane corresponding to the common plane; calculating the quotient of the second area and the first area as an area ratio; generating a second term of the energy equation based on the first area to the area ratio; generating the energy equation from the first term and the second term.
Optionally, the first term is:
Figure BDA0002903292250000031
wherein, ViDenotes the volume of the ith polyhedron, c is the surface probability of the ith polyhedron, liIs the label value of the ith polyhedron,
the second term is:
Figure BDA0002903292250000032
wherein A isi,jA first area, ω, of a common plane of adjacent ith and jth polyhedronsi,jIn the area ratio ofjIs the label value of the jth polyhedron;
the energy equation is:
Figure BDA0002903292250000033
wherein V is the set of all polyhedrons, E is the set of all adjacent polyhedrons, and alpha is a preset equation coefficient.
Optionally, the generating a simplified three-dimensional model corresponding to the original three-dimensional model from the second plane comprises: obtaining a non-plane in the original three-dimensional model; generating the simplified three-dimensional model from the second planar and the non-planar surface.
Optionally, the image segmentation algorithm comprises: graph cut algorithm.
According to a second aspect of the embodiments of the present disclosure, there is provided a model simplification processing apparatus including: the plane acquisition module is used for processing the original three-dimensional model based on a preset plane detection strategy to acquire a first plane in the original three-dimensional model; the segmentation processing module is used for carrying out segmentation processing on a three-dimensional space corresponding to the original three-dimensional model according to the first plane to obtain a geometric element set; wherein the geometric elements include: a polyhedron; the equation building module is used for building an energy equation according to the edge polyhedron positioned at the edge of the three-dimensional space and the common plane information between the adjacent polyhedrons; the equation solving module is used for solving the energy equation by using a preset image segmentation algorithm to obtain tags corresponding to all polyhedrons; wherein the label is used for representing whether the polyhedron is positioned in the interior of the object; a surface determination module for determining at least one first plane belonging to an object surface based on the label, and determining a second plane corresponding to the object surface according to the at least one first plane; and the model generation module is used for generating a simplified three-dimensional model corresponding to the original three-dimensional model according to the second plane.
Optionally, the plane obtaining module is configured to perform plane detection processing on the original three-dimensional model based on a preset plane detection algorithm, so as to obtain a plurality of plane areas in the original three-dimensional model; and determining the boundaries of the plane areas based on a preset boundary determination algorithm to obtain a plurality of first planes.
Optionally, the plane detection method includes: RANSAC, region growing algorithm; the boundary determination algorithm includes: alpha-shape algorithm.
Optionally, the dividing processing module is configured to extend each first plane in the three-dimensional space, so that the first plane divides the space passing through.
Optionally, the surface determination module comprises: the plane distinguishing unit is used for acquiring a first label and a second label corresponding to two adjacent polyhedrons; acquiring a first plane corresponding to a common plane between two adjacent polyhedrons; determining that this first plane belongs to the object surface if the first label and the second label are different.
Optionally, the surface determination module comprises: the plane generating unit is used for acquiring one or more first planes belonging to the surface of an object and generating the second plane based on the one or more first planes.
Optionally, the equation building module is configured to obtain connection line segments between the center of the polyhedron and the centers of the edge polyhedrons respectively; determining the intersection times of each connecting line segment and the intersection times of the composition surfaces of other polyhedrons; calculating the quotient of the number of the connecting line segments with the odd number of intersection times and the total number of the connecting line segments as the surface probability corresponding to the polyhedron; wherein the surface probability is used to characterize whether the polyhedron has an object surface; generating a first term of the energy equation according to the volume of the polyhedron and the corresponding surface probability; acquiring a first area of a common plane between adjacent polyhedrons; acquiring a second area of the first plane corresponding to the common plane; calculating the quotient of the second area and the first area as an area ratio; generating a second term of the energy equation based on the first area to the area ratio; generating the energy equation from the first term and the second term.
Optionally, the first term is:
Figure BDA0002903292250000041
wherein, ViDenotes the volume of the ith polyhedron, c is the surface probability of the ith polyhedron, liIs the label value of the ith polyhedron,
the second term is:
Figure BDA0002903292250000051
wherein A isi,jA first area, ω, of a common plane of adjacent ith and jth polyhedronsi,jIn the area ratio ofjIs the label value of the jth polyhedron;
the energy equation is:
Figure BDA0002903292250000052
wherein V is the set of all polyhedrons, E is the set of all adjacent polyhedrons, and alpha is a preset equation coefficient.
Optionally, the model generation module is configured to obtain a non-plane in the original three-dimensional model; generating the simplified three-dimensional model from the second planar and the non-planar surface.
Optionally, the image segmentation algorithm comprises: graph cut algorithm.
According to a third aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium storing a computer program for executing the above-mentioned method.
According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including: a processor; a memory for storing the processor-executable instructions; the processor is used for executing the method.
Based on the model simplification processing method and device, the electronic equipment and the storage medium provided by the embodiment of the disclosure, structural characteristics in the original three-dimensional model can be kept, and the complexity of the model is reduced while the accuracy is not lost; the calculation complexity is low and the efficiency is high; the real-time performance of three-dimensional model transmission and browsing is improved, and the customer experience is effectively improved.
The technical solution of the present disclosure is further described in detail by the accompanying drawings and examples.
Drawings
The above and other objects, features and advantages of the present disclosure will become more apparent by describing in more detail embodiments of the present disclosure with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of the embodiments of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the principles of the disclosure and not to limit the disclosure. In the drawings, like reference numbers generally represent like parts or steps.
FIG. 1 is a flow diagram of one embodiment of a model reduction processing method of the present disclosure;
FIG. 2 is a flow chart of obtaining a first plane in an original three-dimensional model in one embodiment of a model reduction processing method of the present disclosure;
FIG. 3 is a flow chart of determining a first plane belonging to a surface of an object in an embodiment of a model reduction processing method of the present disclosure;
FIG. 4 is a flow diagram of constructing an energy equation in one embodiment of a model reduction processing method of the present disclosure;
FIGS. 5A, 5B, 5C and 5D are schematic diagrams of a process for generating a simplified three-dimensional model based on an original three-dimensional model;
FIGS. 6A and 6B are schematic diagrams of a segmentation process performed on a three-dimensional space corresponding to the original three-dimensional model;
FIG. 7 is a schematic block diagram of one embodiment of a model reduction processing apparatus of the present disclosure;
FIG. 8 is a structural schematic diagram of a surface determination module in one embodiment of the model reduction processing apparatus of the present disclosure;
FIG. 9 is a block diagram of one embodiment of an electronic device of the present disclosure.
Detailed Description
Example embodiments according to the present disclosure will be described in detail below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely a subset of the embodiments of the present disclosure and not all embodiments of the present disclosure, with the understanding that the present disclosure is not limited to the example embodiments described herein.
It should be noted that: the relative arrangement of parts and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.
It will be understood by those of skill in the art that the terms "first," "second," and the like in the embodiments of the present disclosure are used merely to distinguish one element from another, and are not intended to imply any particular technical meaning, nor is the necessary logical order between them.
It is also understood that in embodiments of the present disclosure, "a plurality" may refer to two or more than two and "at least one" may refer to one, two or more than two.
It is also to be understood that any reference to any component, data, or structure in the embodiments of the disclosure, may be generally understood as one or more, unless explicitly defined otherwise or stated otherwise.
In addition, the term "and/or" in the present disclosure is only one kind of association relationship describing the associated object, and means that there may be three kinds of relationships, such as a and/or B, and may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" in the present disclosure generally indicates that the former and latter associated objects are in an "or" relationship.
It should also be understood that the description of the various embodiments of the present disclosure emphasizes the differences between the various embodiments, and the same or similar parts may be referred to each other, and thus, for brevity, detailed description is not repeated.
Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual scale relationship for the convenience of description.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
Embodiments of the present disclosure may be implemented in electronic devices such as terminal devices, computer systems, servers, etc., which are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known terminal devices, computing systems, environments, and/or configurations that may be suitable for use with an electronic device, such as a terminal device, computer system, or server, include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, networked personal computers, minicomputer systems, mainframe computer systems, distributed cloud computing environments that include any of the above, and the like.
Electronic devices such as terminal devices, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc. that perform particular tasks or implement particular abstract data types. The computer system/server may be implemented in a distributed cloud computing environment. In a distributed cloud computing environment, tasks may be performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices.
Summary of the application
When the three-dimensional model is simplified, the two indexes of the precision and the complexity of the model cannot be simultaneously met, and the high-precision model is high in complexity and not beneficial to real-time rendering. In order to achieve a dynamic balance between the two indexes of precision and complexity, the model simplification method in the prior art is to simplify a three-dimensional model after obtaining the high-precision three-dimensional model, so that the complexity of the model is greatly reduced while the model precision is kept. The existing model simplification method usually adopts an iteration mode, and two edges with the minimum cost loss value are selected in each iteration to carry out edge collapse operation.
In the process of implementing the present disclosure, the inventors find that, although the existing model simplification algorithm is low in computational complexity and high in efficiency, in iteration, the accuracy of the model is reduced, and structural features of the three-dimensional model, such as a plane, are not utilized, so that the finally obtained model does not reach a global optimal solution.
The model simplification processing method provided by the disclosure is used for segmenting a three-dimensional space based on a plane in an original three-dimensional model to obtain a polyhedron; constructing an energy equation according to the edge polyhedrons and the common plane information between the adjacent polyhedrons; solving an energy equation, acquiring labels corresponding to all polyhedrons and used for representing whether the polyhedrons are located inside the object, and generating a simplified three-dimensional model based on the labels; structural characteristics in the original three-dimensional model can be kept, and the complexity of the model is reduced while the accuracy is not lost.
Exemplary method
Fig. 1 is a flowchart of an embodiment of a model simplification processing method of the present disclosure, and the method shown in fig. 1 includes the steps of: S101-S105. The following describes each step.
S101, processing the original three-dimensional model based on a preset plane detection strategy to obtain a first plane in the original three-dimensional model.
In one embodiment, a three-dimensional point cloud for furniture, rooms, etc. is collected, modeled based on the three-dimensional point cloud, and an original three-dimensional model is generated. The original three-dimensional model may be a triangular mesh model, a quadrilateral mesh model, a pentagonal mesh model, or the like. A plane detection strategy may be preset for obtaining a first plane in the original three-dimensional model, where the first plane may be a plane corresponding to a wall, a floor, a ceiling, etc. in the original three-dimensional model.
S102, carrying out segmentation processing on a three-dimensional space corresponding to the original three-dimensional model according to the first plane to obtain a geometric element set. The geometric elements comprise polyhedrons and the like, and the polyhedrons can be tetrahedrons, pentahedrons and the like.
S103, constructing an energy equation according to the edge polyhedron positioned at the edge of the three-dimensional space and the common plane information between the adjacent polyhedrons.
And S104, solving the energy equation by using a preset image segmentation algorithm, and acquiring labels corresponding to all polyhedrons, wherein the labels are used for representing whether the polyhedrons are positioned in the object.
In one embodiment, the object is a wall, floor, ceiling, etc. in an original three-dimensional model, located within a room, including a living room, bedroom, dining room, kitchen, bathroom, etc. The image segmentation algorithm may be various, such as a graph cut algorithm.
S105, determining at least one first plane belonging to the surface of the object based on the label, and determining a second plane corresponding to the surface of the object according to the at least one first plane.
In one embodiment, one or more first planes belonging to a surface of an object (e.g., a wall, a floor, a ceiling, etc.) are obtained, and a second plane is generated based on the one or more first planes; the second plane may be generated using a variety of existing methods, such that multiple first planes are merged into the same second plane.
And S106, generating a simplified three-dimensional model corresponding to the original three-dimensional model according to the second plane.
In one embodiment, where a non-planar surface is obtained in the original three-dimensional model, the simplified three-dimensional model may be generated from the second planar and non-planar surfaces using a variety of existing methods.
In the existing model simplification processing method, because errors may exist in the data acquisition process, after an established original three-dimensional model (for example, a triangular mesh model), triangular surface pieces corresponding to the same feature structures (for example, a wall surface, a ground surface, and the like) are not in the same plane, so that the three-dimensional model obtained through simplification also has the same problem, and the precision of the simplified three-dimensional model is reduced.
According to the model simplification processing method, the structural characteristics in the original three-dimensional model can be kept in the simplified three-dimensional model by extracting the structural characteristic planes in the scene and splicing the discrete planes into the continuous three-dimensional model, so that the triangular patches corresponding to the characteristic structures such as walls, floors, ceilings and the like all fall in the same plane, and the complexity of the model can be reduced while the precision is not lost.
Fig. 2 is a flowchart of obtaining a first plane in an original three-dimensional model in an embodiment of the model simplification processing method of the present disclosure, and the method shown in fig. 2 includes the steps of: S201-S202. The following describes each step.
S201, carrying out plane detection processing on the original three-dimensional model based on a preset plane detection algorithm, and obtaining a plurality of plane areas in the original three-dimensional model.
In one embodiment, the plane detection method includes RANSAC (RANdom SAmple Consensus), a region growing algorithm, and the like. The region growing algorithm is an image segmentation technique, and similar pixels and the like are combined to form a region based on a discrimination rule. The plane detection processing is carried out on the original three-dimensional model by using the conventional RANSAC and region growing algorithm, so that a plane region can be obtained.
S202, determining the boundaries of the plane areas based on a preset boundary determination algorithm, and obtaining a plurality of first planes.
In one embodiment, the boundary determination algorithm comprises an alpha-shape algorithm and the like, and the boundary of the plane area is determined by using the existing alpha-shape algorithm and the like. After obtaining a plurality of first planes, extending each first plane in a three-dimensional Space by using a Binary Space Partition (BSP) algorithm and the like, so that the first plane divides the passing Space to generate a three-dimensional plane extension model, and obtaining a geometric element set.
Fig. 3 is a flowchart of determining a first plane belonging to the surface of an object in an embodiment of the model reduction processing method of the present disclosure, and the method shown in fig. 3 includes the steps of: S301-S303. The following describes each step.
S301, acquiring a first label and a second label corresponding to two adjacent polyhedrons.
S302, a first plane corresponding to a common plane between two adjacent polyhedrons is acquired.
S302, if the first label and the second label are different, the first plane is determined to belong to the surface of the object.
FIG. 4 is a flow chart of constructing an energy equation in one embodiment of a model reduction processing method of the present disclosure, the method shown in FIG. 4 including the steps of: S401-S409. The following describes each step.
S401, connecting line segments between the centers of the polyhedrons and the centers of the edge polyhedrons are obtained.
In an embodiment, a plurality of edge polyhedrons may be previously determined in the three-dimensional plane extension model, and the edge polyhedrons are polyhedrons located at edges of the three-dimensional plane extension model.
S402, determining the intersection frequency of each connecting line segment and the intersection of the composition surfaces of other polyhedrons.
S403, calculating the quotient of the number of the connecting line segments with odd number of intersection times and the total number of the connecting line segments as the surface probability corresponding to the polyhedron; wherein the surface probability is used to characterize whether the polyhedron has an object surface.
S404, generating a first term of an energy equation according to the volume of the polyhedron and the corresponding surface probability.
In one embodiment, the first term of the energy equation may be:
Figure BDA0002903292250000101
wherein, ViDenotes the volume of the ith polyhedron, c is the surface probability of the ith polyhedron, liIs the label value of the ith polyhedron, i is a natural number.
S405, a first area of a common plane between adjacent polyhedrons is acquired.
In one embodiment, in a three-dimensional plane extension model, a common plane between adjacent polyhedrons is determined, and a first area of the common plane is obtained.
S406, a second area of the first plane corresponding to the common plane is obtained.
In one embodiment, a first plane corresponding to the common plane is determined based on the original three-dimensional model and the three-dimensional plane extension model, and a second area of the first plane is obtained.
S407, a quotient of the second area and the first area is calculated as an area ratio.
S408, a second term of the energy equation is generated based on the first area to area ratio.
In one embodiment, the second term of the energy equation is:
Figure BDA0002903292250000111
wherein A isi,jA first area, ω, of a common plane of adjacent ith and jth polyhedronsi,jIn terms of area ratio, liIs the label value of the ith polyhedron, i is a natural number, ljIs the label value of the jth polyhedron, and j is a natural number.
And S409, generating an energy equation according to the first term and the second term.
In one embodiment, the energy equation is:
Figure BDA0002903292250000112
where V is a set of all polyhedrons, E is a set of all adjacent polyhedrons, α is a preset equation coefficient, and a value of α may be preset, for example, to be 0.5,0.6, and the like.
The Graph cut algorithm is an energy optimization algorithm, and can use the existing Graph cut algorithm to solve an energy equation to obtain labels corresponding to all polyhedrons.
In one embodiment, as shown in FIG. 5A, a pre-built original three-dimensional model is obtained, and a first plane is extracted from the original three-dimensional model using a region growing algorithm or the like, as shown in FIG. 5B. The simplified three-dimensional model (with 840 triangular patches) obtained using the existing iteration-based three-dimensional model simplification method is shown in fig. 5C. Using the model reduction processing method of the present disclosure, a continuous reduced three-dimensional model (having 917 polygon patches) is generated based on the discrete first plane, as shown in fig. 5D. From the above, the simplified three-dimensional model obtained by the model simplification processing method of the present disclosure has higher precision, while retaining the structural features of the indoor scene, that is, patches corresponding to the feature structures (e.g., wall surface, ground surface, etc.) are all on the same plane.
As shown in fig. 6A, the original three-dimensional model is processed based on a plane detection strategy, and a first plane in the original three-dimensional model is obtained. The extracted first plane is used to divide the whole three-dimensional space into a series of points, lines, faces and a set of geometric elements of a polyhedron, and a three-dimensional plane extension model is generated, as shown in fig. 6B.
Each first plane is extended in a three-dimensional Space by adopting a Binary Space Partition (Binary Space Partition) algorithm, namely, each first plane is extended for a certain distance in the three-dimensional Space, and then all the spaces passed by the first planes are divided into two, so that the complexity of the algorithm can be greatly reduced, and meanwhile, the search Space of a subsequent optimization algorithm is reduced.
In one embodiment, a label is set for each polygon, with the label value being 0 or 1, respectively. If the label value is 1, it represents that the polyhedron is inside the object, and if the label value is 0, it represents that the polyhedron is outside the object. For all two adjacent polyhedrons, if the corresponding labels are opposite, the face that the two polyhedrons share (the common plane between adjacent polyhedrons) is part of the object surface. Finally, the set of all such patches constitutes a three-dimensional model of the indoor scene.
Defining the problem of calculating each polyhedron label as a Markov field problem, and establishing the following energy equation:
Figure BDA0002903292250000121
wherein the first term of the energy equation is:
Figure BDA0002903292250000122
vi denotes the volume of each polyhedron, and c denotes the probability that each polyhedron belongs to the inside of an object. Firstly, acquiring a line segment formed by the center of each polyhedron and the center of the polyhedron of the edge of the three-dimensional plane extension model (the edge polyhedron is certain to belong to the outside of an object); then, calculating the times of the intersection of the line segments and the component surfaces (alpha shape corresponding to the characteristic planes of walls, ceilings, bottom plates and the like) of other polyhedrons in the three-dimensional plane extension model; finally, the probability c that each polyhedron belongs to the interior of the object is equal to the total number of line segments with odd number of intersections divided by the total number of all line segments. α is a preset equation coefficient, and the value of α may be preset, for example, 0.5,0.6, etc.
The second term of the energy equation is as follows:
Figure BDA0002903292250000123
wherein A isi,jA first area (i.e., A) being a common plane of adjacent ith and jth polyhedronsi,jThe area of a patch common to two adjacent polyhedrons), ωi,jIs the area covered by the initial point and Ai,jThe ratio of. The energy equation can be solved using a graph cut algorithm.
Exemplary devices
In one embodiment, as shown in fig. 7, the present disclosure provides a model simplification processing apparatus, including: a plane acquisition module 701, a segmentation processing module 702, an equation construction module 703, an equation solving module 704, a surface determination module 705, and a model generation module 706.
The plane obtaining module 701 processes the original three-dimensional model based on a preset plane detection strategy to obtain a first plane in the original three-dimensional model. The segmentation processing module 702 performs segmentation processing on a three-dimensional space corresponding to the original three-dimensional model according to a first plane to obtain a set of geometric elements, where the geometric elements include polygons and the like.
The equation construction module 703 constructs an energy equation based on the edge polyhedrons located at the edge of the three-dimensional space and the common plane information between the adjacent polyhedrons. The equation solving module 704 solves the energy equation by using a preset image segmentation algorithm, and obtains labels corresponding to the polyhedrons, where the labels are used for representing whether the polyhedrons are located inside the object.
The surface determination module 705 determines at least one first plane belonging to the surface of the object based on the label, and determines a second plane corresponding to the surface of the object from the at least one first plane. The model generation module 706 generates a simplified three-dimensional model corresponding to the original three-dimensional model from the second plane.
In one embodiment, the plane obtaining module 701 performs plane detection processing on the original three-dimensional model based on a preset plane detection algorithm to obtain a plurality of plane areas in the original three-dimensional model, and the plane detection method includes: RANSAC, region growing algorithms, etc. The plane obtaining module 701 determines the boundary of the plane area based on a preset boundary determining algorithm to obtain a plurality of first planes, wherein the boundary determining algorithm includes an alpha-shape algorithm and the like.
The division processing module 702 extends each first plane in the three-dimensional space by using a binary space division algorithm, so that the first plane divides the space passing through. The model generation module 707 obtains the non-planar surface in the original three-dimensional model and generates a simplified three-dimensional model from the second planar surface and the non-planar surface.
In one embodiment, the equation building module 703 obtains connecting line segments between the centers of the polyhedrons and the centers of the plurality of edge polyhedrons, respectively. The equation building module 703 determines the number of intersections of each connecting line segment with the component surfaces of other polyhedrons, and calculates the quotient of the number of connecting line segments with odd number of intersections and the total number of connecting line segments as the surface probability corresponding to the polyhedron, where the surface probability is used to represent whether the polyhedron has an object surface.
The equation building module 703 generates a first term of the energy equation from the volume of the polyhedron and the corresponding surface probability. The equation construction module 703 acquires a first area of a common plane between adjacent polyhedrons, acquires a second area of the first plane corresponding to the common plane, calculates a quotient of the second area and the first area as an area ratio, and generates a second term of the energy equation based on the first area and the area ratio. The equation building module 703 generates an energy equation from the first term and the second term.
As shown in fig. 8, the surface determination module 705 includes: plane discriminating section 7051 and plane generating section 7052. Plane discriminating section 7051 acquires a first label and a second label corresponding to two adjacent polyhedrons, and acquires a first plane corresponding to a common plane between the two adjacent polyhedrons. If the first tag and the second tag are different, the plane discrimination unit 7051 determines that this first plane belongs to the surface of the object. Plane generating unit 7052 obtains one or more first planes belonging to a surface of an object, and generates a second plane based on the one or more first planes.
Fig. 9 is a block diagram of one embodiment of an electronic device of the present disclosure, as shown in fig. 9, the electronic device 131 includes one or more processors 911 and memory 912.
The processor 911 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device 91 to perform desired functions.
Memory 912 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. Volatile memory, for example, may include: random Access Memory (RAM) and/or cache memory (cache), etc. The nonvolatile memory, for example, may include: read Only Memory (ROM), hard disk, flash memory, and the like. One or more computer program instructions may be stored on a computer-readable storage medium and executed by processor 911 to implement the model reduction processing methods of the various embodiments of the present disclosure above and/or other desired functionality. Various contents such as an input signal, a signal component, a noise component, etc. may also be stored in the computer-readable storage medium.
In one example, the electronic device 91 may further include: an input device 99, and an output device 914, etc., interconnected by a bus system and/or other form of connection mechanism (not shown). The input device 913 may include, for example, a keyboard, a mouse, or the like. The output device 914 may output various information to the outside. The output devices 914 can include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, among others.
Of course, for simplicity, only some of the components of the electronic device 91 relevant to the present disclosure are shown in fig. 9, omitting components such as buses, input/output interfaces, and the like. In addition, the electronic device 91 may include any other suitable components depending on the particular application.
In addition to the methods and apparatus described above, embodiments of the present disclosure may also be a computer program product comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps in the model reduction processing method according to various embodiments of the present disclosure described in the "exemplary methods" section above of this specification.
The computer program product may write program code for performing the operations of embodiments of the present disclosure in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present disclosure may also be a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, cause the processor to perform steps in a model reduction processing method according to various embodiments of the present disclosure described in the "exemplary methods" section above in this specification.
The computer-readable storage medium may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the above. More specific examples (a non-exhaustive list) of the readable storage medium may include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The foregoing describes the general principles of the present disclosure in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present disclosure are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present disclosure. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the disclosure is not intended to be limited to the specific details so described.
In the model simplification processing method and device, the electronic device and the storage medium in the above embodiments, the three-dimensional space is segmented based on the plane in the original three-dimensional model to obtain a polyhedron; constructing an energy equation according to the edge polyhedrons and the common plane information between the adjacent polyhedrons; solving an energy equation, obtaining labels corresponding to all polyhedrons and used for representing whether the polyhedrons are located inside the object, and generating a simplified three-dimensional model based on the labels; the complexity of the model can be greatly reduced while the precision of the model is kept; structural characteristics in the original three-dimensional model can be kept, so that the surface patches corresponding to characteristic structures such as walls, floors, ceilings and the like all fall in the same plane, and the complexity of the model is reduced while the accuracy is not lost; the calculation complexity is low and the efficiency is high; the real-time performance of three-dimensional model transmission and browsing is improved, and the customer experience is effectively improved.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts in the embodiments are referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The block diagrams of devices, apparatuses, systems referred to in this disclosure are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, and systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".
The methods and apparatus of the present disclosure may be implemented in a number of ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present disclosure may also be implemented as a program recorded in a recording medium, the program including machine-readable instructions for implementing a method according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.
It is also noted that in the devices, apparatuses, and methods of the present disclosure, each component or step can be decomposed and/or recombined. These decompositions and/or recombinations are to be considered equivalents of the present disclosure.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects, and the like, will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, the description is not intended to limit embodiments of the disclosure to the form disclosed herein. While a number of example aspects and embodiments have been discussed above, those of skill in the art will recognize certain variations, modifications, alterations, additions and sub-combinations thereof.

Claims (10)

1. A model reduction processing method, comprising:
processing an original three-dimensional model based on a preset plane detection strategy to obtain a first plane in the original three-dimensional model;
carrying out segmentation processing on a three-dimensional space corresponding to the original three-dimensional model according to the first plane to obtain a geometric element set; wherein the geometric elements include: a polyhedron;
constructing an energy equation according to edge polyhedrons located at the edges of the three-dimensional space and common plane information between adjacent polyhedrons;
solving the energy equation by using a preset image segmentation algorithm to obtain labels corresponding to all polyhedrons; wherein the label is used for representing whether the polyhedron is positioned in the interior of the object;
determining at least one first plane belonging to the surface of the object based on the label and determining a second plane corresponding to the surface of the object according to the at least one first plane;
and generating a simplified three-dimensional model corresponding to the original three-dimensional model according to the second plane.
2. The method of claim 1, wherein the processing the original three-dimensional model based on a preset plane detection strategy, and obtaining the first plane in the original three-dimensional model comprises:
carrying out plane detection processing on the original three-dimensional model based on a preset plane detection algorithm to obtain a plurality of plane areas in the original three-dimensional model;
and determining the boundaries of the plane areas based on a preset boundary determination algorithm to obtain a plurality of first planes.
3. The method of claim 2, wherein,
the plane detection method comprises the following steps: at least one of RANSAC, region growing algorithm;
the boundary determination algorithm includes: alpha-shape algorithm.
4. The method of claim 1, wherein said segmenting a three-dimensional space corresponding to the original three-dimensional model according to the first plane, obtaining a set of geometric elements comprises:
each first plane is extended in the three-dimensional space, so that the first plane divides the passing space.
5. The method of claim 1, the determining at least one first plane that belongs to a surface of an object based on the tag comprising:
acquiring a first label and a second label corresponding to two adjacent polyhedrons;
acquiring a first plane corresponding to a common plane between two adjacent polyhedrons;
determining that this first plane belongs to the object surface if the first label and the second label are different.
6. The method of claim 1, the determining a second plane corresponding to the object surface based on the at least one first plane comprising:
acquiring one or more first planes belonging to the surface of an object;
generating the second plane based on the one or more first planes.
7. The method of claim 1, wherein constructing an energy equation based on edge polyhedrons located at the edges of the three-dimensional space and common plane information between adjacent polyhedrons comprises:
acquiring connecting line segments between the centers of the polyhedrons and the centers of a plurality of edge polyhedrons respectively;
determining the intersection times of each connecting line segment and the intersection times of the composition surfaces of other polyhedrons;
calculating the quotient of the number of the connecting line segments with the odd number of intersection times and the total number of the connecting line segments as the surface probability corresponding to the polyhedron; wherein the surface probability is used to characterize whether the polyhedron has an object surface;
generating a first term of the energy equation according to the volume of the polyhedron and the corresponding surface probability;
acquiring a first area of a common plane between adjacent polyhedrons;
acquiring a second area of the first plane corresponding to the common plane;
calculating the quotient of the second area and the first area as an area ratio;
generating a second term of the energy equation based on the first area to the area ratio;
generating the energy equation from the first term and the second term.
8. A model reduction processing apparatus comprising:
the plane acquisition module is used for processing the original three-dimensional model based on a preset plane detection strategy to acquire a first plane in the original three-dimensional model;
the segmentation processing module is used for carrying out segmentation processing on a three-dimensional space corresponding to the original three-dimensional model according to the first plane to obtain a geometric element set; wherein the geometric elements include: a polyhedron;
the equation building module is used for building an energy equation according to the edge polyhedron positioned at the edge of the three-dimensional space and the common plane information between the adjacent polyhedrons;
the equation solving module is used for solving the energy equation by using a preset image segmentation algorithm to obtain labels corresponding to all polyhedrons; wherein the label is used for representing whether the polyhedron is positioned in the interior of the object;
a surface determination module for determining at least one first plane belonging to an object surface based on the label, and determining a second plane corresponding to the object surface according to the at least one first plane;
and the model generation module is used for generating a simplified three-dimensional model corresponding to the original three-dimensional model according to the second plane.
9. A computer-readable storage medium, the storage medium storing a computer program for performing the method of any of the preceding claims 1-7.
10. An electronic device, the electronic device comprising:
a processor; a memory for storing the processor-executable instructions;
the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method of any one of claims 1-7.
CN202110063539.1A 2021-01-18 2021-01-18 Model simplification processing method and device, electronic equipment and medium Active CN112991547B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110063539.1A CN112991547B (en) 2021-01-18 2021-01-18 Model simplification processing method and device, electronic equipment and medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110063539.1A CN112991547B (en) 2021-01-18 2021-01-18 Model simplification processing method and device, electronic equipment and medium

Publications (2)

Publication Number Publication Date
CN112991547A true CN112991547A (en) 2021-06-18
CN112991547B CN112991547B (en) 2022-05-17

Family

ID=76344415

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110063539.1A Active CN112991547B (en) 2021-01-18 2021-01-18 Model simplification processing method and device, electronic equipment and medium

Country Status (1)

Country Link
CN (1) CN112991547B (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113628328A (en) * 2021-08-12 2021-11-09 深圳须弥云图空间科技有限公司 Model rendering method and device for abutted seam component
CN113781667A (en) * 2021-11-10 2021-12-10 深圳大学 Three-dimensional structure simplified reconstruction method and device, computer equipment and storage medium
CN116452770A (en) * 2023-02-17 2023-07-18 北京德风新征程科技股份有限公司 Three-dimensional model reconstruction method, device, equipment and medium

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102855663A (en) * 2012-05-04 2013-01-02 北京建筑工程学院 Method for building CSG (Constructive Solid Geometry) model according to laser radar grid point cloud
CN110298922A (en) * 2019-07-04 2019-10-01 浙江科澜信息技术有限公司 A kind of three-dimensional model simplifying method, device and equipment
CN110997286A (en) * 2017-08-07 2020-04-10 Eos有限公司电镀光纤系统 Optimized partitioning method
CN111508074A (en) * 2020-03-12 2020-08-07 浙江工业大学 Three-dimensional building model simplification method based on roof contour line

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102855663A (en) * 2012-05-04 2013-01-02 北京建筑工程学院 Method for building CSG (Constructive Solid Geometry) model according to laser radar grid point cloud
CN110997286A (en) * 2017-08-07 2020-04-10 Eos有限公司电镀光纤系统 Optimized partitioning method
CN110298922A (en) * 2019-07-04 2019-10-01 浙江科澜信息技术有限公司 A kind of three-dimensional model simplifying method, device and equipment
CN111508074A (en) * 2020-03-12 2020-08-07 浙江工业大学 Three-dimensional building model simplification method based on roof contour line

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
YI, BING等: "Triangulated surface flattening based on the physical shell model", 《JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY》 *
朱运芝: "面向绘制的三维模型优化", 《中国优秀硕士学位论文全文数据库 (信息科技辑)》 *
沈丞等: "虚拟演播室中三维模型简化算法研究", 《电视技术》 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113628328A (en) * 2021-08-12 2021-11-09 深圳须弥云图空间科技有限公司 Model rendering method and device for abutted seam component
CN113781667A (en) * 2021-11-10 2021-12-10 深圳大学 Three-dimensional structure simplified reconstruction method and device, computer equipment and storage medium
CN113781667B (en) * 2021-11-10 2022-03-11 深圳大学 Three-dimensional structure simplified reconstruction method and device, computer equipment and storage medium
CN116452770A (en) * 2023-02-17 2023-07-18 北京德风新征程科技股份有限公司 Three-dimensional model reconstruction method, device, equipment and medium
CN116452770B (en) * 2023-02-17 2023-10-20 北京德风新征程科技股份有限公司 Three-dimensional model reconstruction method, device, equipment and medium

Also Published As

Publication number Publication date
CN112991547B (en) 2022-05-17

Similar Documents

Publication Publication Date Title
CN112991547B (en) Model simplification processing method and device, electronic equipment and medium
JP6998964B2 (en) Methods and equipment for determining the geofence index grid
CN112767551B (en) Three-dimensional model construction method and device, electronic equipment and storage medium
US10417821B2 (en) Method of simplifying a geometry model
US10282636B2 (en) System, method, and recording medium for efficient cohesive subgraph identification in entity collections for inlier and outlier detection
US8954295B1 (en) Determining an outer shell of a composite three-dimensional model
CN112765709B (en) House type graph reconstruction method and device based on point cloud data
CN110263493A (en) A kind of room construction area calculation method and device based on REVIT
CN113470095A (en) Processing method and device for indoor scene reconstruction model
US8935129B1 (en) System and method for simplifying a graph'S topology and persevering the graph'S semantics
CN113971307A (en) Incidence relation generation method and device, storage medium and electronic equipment
CN111080792B (en) Model simplification processing method and device, electronic equipment and storage medium
JP7369288B2 (en) Image processing method, image processing command generation method and device
EP2899695A1 (en) Method, system and computer program product for 3D objects graphical representation
CN113538562B (en) Indoor area determination method and device, electronic equipment and storage medium
CN111340100A (en) Similarity calculation method of BIM (building information modeling) model
WO2023164933A1 (en) Building modeling method and related apparatus
CN115033616A (en) Data screening rule verification method and device based on multi-round sampling
CN114329743A (en) House type optimization method, device and storage medium
CN110837707B (en) Finite element analysis system, method, computer equipment and storage medium
US10930072B1 (en) Multi-resolution mesh real-time contouring
CN116681857A (en) Space collision detection method and device and electronic equipment
CN115690120B (en) Method, apparatus, device, medium and program product for generating three-dimensional grid
CN111612069A (en) Density clustering method and device based on dynamic grid Hash index
CN117473331B (en) Stream data processing method, device, equipment and storage medium

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
TA01 Transfer of patent application right
TA01 Transfer of patent application right

Effective date of registration: 20210926

Address after: 100085 Floor 101 102-1, No. 35 Building, No. 2 Hospital, Xierqi West Road, Haidian District, Beijing

Applicant after: Seashell Housing (Beijing) Technology Co.,Ltd.

Address before: 101300 room 24, 62 Farm Road, Erjie village, Yangzhen Town, Shunyi District, Beijing

Applicant before: Beijing fangjianghu Technology Co.,Ltd.

GR01 Patent grant
GR01 Patent grant