CN117934702A - Reverse modeling method, device, computer equipment and storage medium - Google Patents
Reverse modeling method, device, computer equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of modeling, and discloses a reverse modeling method, a device, computer equipment and a storage medium, wherein the method comprises the following steps: acquiring a target three-dimensional point cloud model of a target object; slicing the target three-dimensional point cloud model to obtain contour point clouds of different heights of a target object in a normal direction, wherein the normal direction is any one of the dimension directions predefined based on the target object; linearly fitting the contour point cloud of each height to obtain a contour line of each height; and (5) carrying out reverse modeling based on contour lines of all heights to obtain a solid model of the target object. According to the invention, the contour point clouds of different heights of the target object in the normal direction are obtained by slicing the target three-dimensional point cloud model, the contour point clouds of each height are linearly fitted to obtain the contour line of each height, and the reverse modeling is performed based on the contour lines of all heights, so that the automatic reverse modeling of all the target three-dimensional point cloud models is realized.
Description
Technical Field
The invention relates to the technical field of modeling, in particular to a reverse modeling method, a reverse modeling device, computer equipment and a storage medium.
Background
The three-dimensional laser scanning technology is a high-precision building measurement technology, and is characterized in that a laser scanner is used for scanning a building to obtain point cloud data on the surface of the building, and then the three-dimensional model is generated through processing and reconstruction of the point cloud data. The technology can rapidly and accurately acquire the geometric shape, structure and detail information of the building, and provides important data support for the design, construction and maintenance of the building.
BIM (Building Information Modeling, building information model) is a building information management technology based on digital modeling, which integrates various information (including geometry, structure, equipment, materials, etc.) of a building into a unified model, thus realizing the full life cycle management of the building. BIM technology can provide efficient and accurate information support in various stages of building design, construction, operation, maintenance and the like, and help project managers and participants to better cooperate and make decisions.
The combination of the three-dimensional laser scanning technology and the BIM technology can realize high-precision digital modeling of the building, and provides more accurate and efficient data support for the design, construction and maintenance of the building. Specifically, the three-dimensional laser scanning technology can rapidly acquire geometric shape and structure information of a building, the BIM technology can integrate the information into a comprehensive model, and more information such as equipment, materials, construction progress and the like is added into the model, so that full life cycle management of the building is realized. Meanwhile, the BIM technology can also introduce the point cloud data acquired by the three-dimensional laser scanning technology into the model, so that finer modeling and analysis of the building are realized, and the design and construction quality of the building are improved.
The real scene point cloud data acquired by three-dimensional laser scanning can be used for design, operation and maintenance and the like by reverse modeling in software for building a BIM model. The existing reverse modeling plug-in can be used for rapidly modeling a wall body, a column body, a steel structure and a water pipe, the principle is that the parameterization modeling is performed by utilizing characteristic fitting of the plug-in, for example, the wall body position, the wall thickness, the elevation and other parameters are determined, a wall model can be built, but uniform parameters cannot be obtained for special-shaped components such as curved surfaces, cambered surfaces and the like, so that the reverse modeling cannot be performed by the method. And the artificial reverse modeling is long in time consumption and low in efficiency, and the application of the three-dimensional scanning technology in the building industry is hindered.
Disclosure of Invention
In view of the above, the invention provides a reverse modeling method, a device, a computer device and a storage medium, so as to solve the problem that the existing reverse modeling plug-in cannot model a special-shaped component and the time is consumed for manual reverse modeling.
In a first aspect, the present invention provides a reverse modeling method, the method comprising:
Acquiring a target three-dimensional point cloud model of a target object;
Slicing the target three-dimensional point cloud model to obtain contour point clouds of different heights of the target object in the normal direction, wherein the normal direction is any one dimension direction predefined based on the target object;
Linearly fitting the contour point cloud of each height to obtain a contour line of each height;
and (5) carrying out reverse modeling based on contour lines of all heights to obtain a solid model of the target object.
According to the reverse modeling method provided by the embodiment, the contour point clouds of different heights of the target object in the normal direction are obtained by slicing the target three-dimensional point cloud model, the contour point clouds of each height are linearly fitted to obtain the contour line of each height, and the reverse modeling is performed based on the contour lines of all heights, so that the automatic reverse modeling of all the target objects is realized, and compared with the manual reverse modeling, the reverse modeling method provided by the embodiment is short in time consumption and high in efficiency.
In an optional implementation manner, the slicing processing is performed on the target three-dimensional point cloud model to obtain contour point clouds of different heights of the target object in a normal direction, including:
Determining a tangential plane of the target three-dimensional point cloud model, wherein the tangential plane is perpendicular to the normal direction;
And slicing the target three-dimensional point cloud model based on the slicing plane to obtain contour point clouds with different heights of the target object in the normal direction.
In an alternative embodiment, the linearly fitting the contour point cloud of each height to obtain a contour line of each height includes:
Dividing the outline point cloud of each height into an upper layer point cloud and a lower layer point cloud by taking the middle surface of the outline point cloud of each height as a reference surface;
The shortest Euclidean distance is used as a searching target, the upper layer point cloud and the lower layer point cloud of each height are paired one by one, and the paired upper layer point cloud and lower layer point cloud are connected by utilizing a straight line;
acquiring a set of intersections of the straight lines and the reference surface at each height;
And connecting the intersection points in the intersection point set of each height to obtain the contour line of each height.
In an alternative embodiment, the determining the tangent plane of the target three-dimensional point cloud model includes:
Determining the thickness of the contour point cloud based on the point cloud density, wherein the thickness is the thickness in the normal direction;
Determining the number of tangential planes of the target three-dimensional point cloud model based on the thickness of the contour point cloud;
The slicing processing is performed on the target three-dimensional point cloud model based on the slicing plane to obtain contour point clouds of different heights of the target object in the normal direction, including:
And slicing the target three-dimensional point cloud model based on the thickness of the contour point cloud and the number of tangential planes to obtain contour point clouds with different heights of the target object in the normal direction.
In an alternative embodiment, the connecting the intersection points in the intersection point set of each height to obtain the contour line of each height includes:
Determining a first intersection point and a second intersection point in the intersection point set of each height based on the intersection point coordinates, wherein the first intersection point is an intersection point with the largest intersection point X coordinate in the intersection point set of each height, and the second intersection point is an intersection point with the smallest intersection point X coordinate in the intersection point set of each height;
The first intersection point and the second intersection point are connected through a straight line, and the intersection point set of each height is divided into a first intersection point set and a second intersection point set;
Ordering the intersection points in the first intersection point set and the second intersection point set based on the intersection point coordinates to obtain a third intersection point set and a fourth intersection point set;
combining the third intersection point set and the fourth intersection point set to obtain contour line sequence arrangement point sets of each height;
and connecting the intersection points according to the sequence of the intersection points in the point set arranged in the sequence of the contour lines of each height, and obtaining the contour lines of each height.
In an alternative embodiment, determining the normal direction of the target object by:
And acquiring a core dimension of the target object, and determining the core dimension as a normal direction, wherein the core dimension is the dimension with the longest dimension length in the target object.
In an alternative embodiment, the acquiring the target three-dimensional point cloud model of the target object includes:
Acquiring a three-dimensional point cloud model of a target object through a three-dimensional laser scanning technology;
And preprocessing the three-dimensional point cloud model to obtain a target three-dimensional point cloud model.
In a second aspect, the present invention provides a reverse modeling apparatus, the apparatus comprising:
the target three-dimensional point cloud model acquisition module is used for acquiring a target three-dimensional point cloud model of a target object;
The contour point cloud acquisition module is used for carrying out slicing processing on the target three-dimensional point cloud model to obtain contour point clouds with different heights of the target object in the normal direction, wherein the normal direction is any one dimension direction predefined based on the target object;
The contour line acquisition module is used for carrying out linear fitting on the contour point cloud of each height to obtain a contour line of each height;
And the solid model acquisition module is used for carrying out reverse modeling based on the contour lines of all the heights to obtain a solid model of the target object.
In a third aspect, the present invention provides a computer device comprising: the device comprises a memory and a processor, wherein the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions, so that the reverse modeling method of the first aspect or any implementation mode corresponding to the first aspect is executed.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon computer instructions for causing a computer to perform the reverse modeling method of the first aspect or any of its corresponding embodiments.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow diagram of a reverse modeling method according to an embodiment of the present invention;
FIG. 2 is a flow diagram of another reverse modeling method according to an embodiment of the present invention;
FIG. 3 is a schematic view of a tangential plane in accordance with an embodiment of the invention;
FIG. 4 (a) is a schematic diagram of a connection between a first intersection point and a second intersection point according to an embodiment of the present invention;
FIG. 4 (b) is a schematic diagram of the ordering of a first set of intersections and a second set of intersections according to an embodiment of the invention;
FIG. 4 (c) is a schematic diagram of generating a contour line according to an embodiment of the present invention;
fig. 5 (a) is a schematic diagram of a fitted contour line of a helmet according to an embodiment of the present invention;
fig. 5 (b) is a schematic diagram of a reverse modeling effect of a helmet according to an embodiment of the present invention;
FIG. 6 (a) is a schematic diagram of a three-dimensional point cloud model of a welded eccentric reducer according to an embodiment of the invention;
FIG. 6 (b) is a schematic diagram of the reverse modeling effect of the welded eccentric reducer according to an embodiment of the present invention;
FIG. 7 is a block diagram of a reverse modeling apparatus according to an embodiment of the present invention;
Fig. 8 is a schematic diagram of a hardware structure of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The combination of the three-dimensional laser scanning technology and the BIM technology can realize high-precision digital modeling of the building, and provides more accurate and efficient data support for the design, construction and maintenance of the building. Specifically, the three-dimensional laser scanning technology can rapidly acquire geometric shape and structure information of a building, the BIM technology can integrate the information into a comprehensive model, and more information such as equipment, materials, construction progress and the like is added into the model, so that full life cycle management of the building is realized. Meanwhile, the BIM technology can also introduce the point cloud data acquired by the three-dimensional laser scanning technology into the model, so that finer modeling and analysis of the building are realized, and the design and construction quality of the building are improved.
The real scene point cloud data acquired by three-dimensional laser scanning can be used for design, operation and maintenance and the like by reverse modeling in software for building a BIM model. The existing reverse modeling plug-in can be used for rapidly modeling a wall body, a column body, a steel structure and a water pipe, the principle is that the parameterization modeling is performed by utilizing characteristic fitting of the plug-in, for example, the wall body position, the wall thickness, the elevation and other parameters are determined, a wall model can be built, but uniform parameters cannot be obtained for special-shaped components such as curved surfaces, cambered surfaces and the like, so that the reverse modeling cannot be performed by the method. And the artificial reverse modeling is long in time consumption and low in efficiency, and the application of the three-dimensional scanning technology in the building industry is hindered.
The embodiment of the invention provides a reverse modeling method, which is characterized in that contour point clouds of different heights of a target object in a normal direction are obtained by slicing a target three-dimensional point cloud model, linear fitting is carried out on the contour point clouds of each height to obtain contour lines of each height, and reverse modeling is carried out on the basis of the contour lines of all the heights, so that the effect of automatically realizing reverse modeling on all the target three-dimensional point cloud models is achieved.
In accordance with an embodiment of the present invention, an inverse modeling method embodiment is provided, it being noted that the steps shown in the flowchart of the figures may be performed in a computer system, such as a set of computer executable instructions, and, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in an order other than that shown or described herein.
In this embodiment, a reverse modeling method is provided, which may be used in the above mobile terminal, such as a central processing unit, a server, etc., and fig. 1 is a flowchart of the reverse modeling method according to an embodiment of the present invention, as shown in fig. 1, where the flowchart includes the following steps:
Step S101, a target three-dimensional point cloud model of a target object is obtained.
The embodiment obtains a target three-dimensional point cloud model of a target object through a three-dimensional laser scanning technology.
The target object may be a building such as a wall, a main body, a steel plate water pipe, or a building having a special-shaped member such as a curved surface or an arc surface.
It should be noted that, in this embodiment, the target three-dimensional point cloud model of the target object is reversely modeled by the Dynamo visual programming platform. Dynamo, the visual programming platform reads a target three-dimensional point cloud model obtained by a three-dimensional laser scanning technology, wherein the Dynamo visual programming platform imports the target three-dimensional point cloud model through a data.Import excel command.
In an optional embodiment, dynamo the visual programming platform performs thinning processing and sparse display on the target three-dimensional point cloud model through a list.slice command. The method can simplify the display of the three-dimensional point cloud model of the target and accelerate the operation speed.
Step S102, slicing the target three-dimensional point cloud model to obtain contour point clouds of different heights of the target object in the normal direction.
Wherein the normal direction is any dimension direction predefined based on the target object.
After the target three-dimensional point cloud model is obtained, the Dynamo visual programming platform carries out slicing processing on the target three-dimensional point cloud model to obtain contour point clouds of different heights of the target object in the normal direction.
It can be understood that slicing is performed on the target three-dimensional point cloud model in the normal direction to obtain contour point clouds with different heights.
And step S103, performing linear fitting on the contour point cloud of each height to obtain a contour line of each height.
After the contour point clouds of different heights of the target object in the normal direction are obtained, the contour point clouds of different heights are converted into contour lines from discrete points.
In the linear fitting of the contour point cloud for each height, it is necessary to perform point interpolation for the contour point cloud for each height by using the idea of the least squares method.
And step S104, performing reverse modeling based on contour lines of all heights to obtain a solid model of the target object.
Specifically, after the contour lines of each height are obtained, the Dynamo visual programming platform performs inverse modeling according to the contour lines of all heights to obtain a solid model of the target object, namely, a BIM model of the target object.
According to the reverse modeling method provided by the embodiment, the contour point clouds of different heights of the target object in the normal direction are obtained by slicing the target three-dimensional point cloud model, the contour point clouds of each height are linearly fitted to obtain the contour line of each height, and the reverse modeling is performed based on the contour lines of all heights, so that the automatic reverse modeling of all the target objects is realized, and compared with the manual reverse modeling, the reverse modeling method provided by the embodiment is short in time consumption and high in efficiency.
In this embodiment, a reverse modeling method is provided, which may be used in the above mobile terminal, such as a central processing unit, a server, etc., and fig. 2 is a flowchart of the reverse modeling method according to an embodiment of the present invention, as shown in fig. 2, where the flowchart includes the following steps:
step S201, a target three-dimensional point cloud model of the target object is acquired.
Specifically, the step S201 includes:
Step S2011, a three-dimensional point cloud model of the target object is obtained through a three-dimensional laser scanning technology.
And scanning the target object through a laser scanner to obtain a three-dimensional point cloud model of the surface of the target object.
Step S2012, preprocessing the three-dimensional point cloud model to obtain a target three-dimensional point cloud model.
Wherein, preprocessing comprises registering, classifying, cutting, denoising, downsampling, deriving and the like of the three-dimensional point cloud model.
It should be noted that, the preprocessing of the three-dimensional point cloud model is to obtain a more accurate three-dimensional point cloud model of the target object, so as to obtain a more accurate solid model.
And after preprocessing the three-dimensional point cloud model of the target object, obtaining the target three-dimensional point cloud model.
It should be further noted that, in this embodiment, the three-dimensional point cloud model is preprocessed by specialized point cloud processing software, and an ASCII closed format is derived, where the point cloud space information of the target three-dimensional point cloud model may be displayed in an Excel document format.
Step S202, slicing the target three-dimensional point cloud model to obtain contour point clouds of different heights of the target object in the normal direction.
Specifically, the step S202 includes:
in step S2021, a tangential plane of the target three-dimensional point cloud model is determined.
Wherein the tangential plane is perpendicular to the normal direction.
It can be appreciated that, to slice the target three-dimensional point cloud model, a tangential plane of the target three-dimensional point cloud model needs to be determined first.
Illustratively, as shown in fig. 3, EI, E, er are schematic tangential planes, the normal direction is the Z-axis direction, the XOY coordinate system is selected by the user in the point cloud processing software, P1, P2, P3 are the intersection points of the tangential planes and the target three-dimensional point cloud model, and D is the thickness of the contour point cloud.
The length and width of the tangential plane may be the maximum value of the abscissa of the point cloud in the selected target three-dimensional point cloud model, so that a minimum envelope box of the contour point cloud can be established, and the point cloud in the envelope box is processed.
In step S2022, slicing is performed on the target three-dimensional point cloud model based on the tangent plane, so as to obtain contour point clouds of different heights of the target object in the normal direction.
And after determining the tangential plane of the target three-dimensional point cloud model, slicing the target three-dimensional point cloud model by using the tangential plane to obtain contour point clouds of different heights of the target object in the normal direction.
In some alternative embodiments, step S2021 described above comprises:
And a step a1, determining the thickness of the outline point cloud based on the point cloud density.
Wherein the thickness is the thickness in the normal direction.
In order to prevent the error in linear fitting caused by the lack of local information of the point cloud on the tangent plane, the present embodiment introduces a slice threshold, i.e. a slice with a thickness.
The point cloud density is a characteristic quantity reflecting the average minimum unit point distance of the point cloud, a KDTree algorithm can be used for acquiring adjacent points for estimation, and the process is realized by a self-built Python Script node source program.
After the point cloud density is obtained, the point cloud density is determined as the thickness of the contour point cloud.
And a step a2, determining the number of tangential planes of the target three-dimensional point cloud model based on the thickness of the contour point cloud.
It will be appreciated that after the thickness of the contour point cloud is obtained, the number of tangential planes of the target three-dimensional point cloud model can be determined by knowing the height of the target three-dimensional point cloud model.
In some alternative embodiments, step S2022 described above comprises:
and b1, slicing the target three-dimensional point cloud model based on the thickness of the contour point cloud and the number of tangential planes to obtain contour point clouds of different heights of the target object in the normal direction.
After the thickness of the contour point cloud and the number of the tangent planes are obtained, slicing is carried out on the target three-dimensional point cloud model in the normal direction according to the thickness of the contour point cloud and the data of the tangent planes, and the contour point clouds of different heights of the target object in the normal direction are obtained.
Step S203, performing linear fitting on the contour point cloud of each height to obtain a contour line of each height.
Specifically, the step S203 includes:
in step S2031, the contour point clouds of each height are divided into an upper layer point cloud and a lower layer point cloud by taking the middle plane of the contour point clouds of each height as a reference plane.
The middle surface of the contour point cloud refers to a slice surface corresponding to half of the thickness of the contour point cloud.
And dividing the contour point cloud of each height into an upper layer point cloud and a lower layer point cloud based on the reference plane of the contour point cloud of each height. It is understood that in the normal direction, the point cloud above the reference plane is the upper layer point cloud, and the point cloud below the reference plane is the lower layer point cloud.
Step S2032, pairing the upper layer point clouds and the lower layer point clouds of each height one by taking the shortest euclidean distance as a searching target, and connecting the paired upper layer point clouds and lower layer point clouds by using a straight line.
After the profile point clouds of each height are divided into an upper layer point cloud and a lower layer point cloud, the upper layer point cloud and the lower layer point cloud are paired one by taking the shortest Euclidean distance as a searching target, and the upper layer point cloud and the lower layer point cloud which are paired are connected by a straight line.
Step S2033, a set of intersections of each height straight line and the reference plane is acquired.
And after the paired upper layer point cloud and lower layer point cloud of each height are connected by straight lines, acquiring an intersection set of each height straight line and a reference plane.
Step S2034, connecting the intersections in each height intersection set, and obtaining the contour line of each height.
After the intersection point set of each height is obtained, the intersection points in the intersection point set of each height are connected, and the contour line of each height is obtained.
It should be noted that, the first linear fitting of the contour point cloud has a lot of overlapping points, which is easy to generate the risk of interfacial intersection, resulting in running error reporting, and the contour line is subjected to secondary split fitting by using the node Curve.PointAtParameter, so as to obtain a standard closed curve, and then the standard closed curve is reintroduced into the solid.ByLoft node for entity model generation.
In some optional embodiments, step S2034 includes:
and c1, determining a first intersection point and a second intersection point in each height intersection point set based on the intersection point coordinates.
It should be noted that, in this embodiment, when the three-dimensional point cloud model is preprocessed by the professional point cloud processing software, the three-dimensional point cloud model is placed in a coordinate system selected by the user. Wherein the Z axis of the coordinate system is the normal direction of the target object.
After each height intersection point set is obtained, determining a first intersection point and a second intersection point in each height intersection point set according to the coordinates of the intersection points in the intersection point set, wherein the first intersection point is the intersection point with the largest X coordinate in each height intersection point set, and the second intersection point is the intersection point with the smallest X coordinate in each height intersection point set, and the X coordinate is the abscissa.
And c2, connecting the first intersection point and the second intersection point by utilizing a straight line, and dividing each height intersection point set into a first intersection point set and a second intersection point set.
After the first intersection point and the second intersection point in each height intersection point set are determined, connecting the first intersection point and the second intersection point in each height intersection point set by using a straight line, and dividing each height intersection point set into a first intersection point set and a second intersection point set by taking the straight line as a dividing line.
Illustratively, as shown in fig. 4 (a), a is a first intersection in a certain height intersection set, B is a second intersection in a certain height intersection set, and the intersection set is divided into two regions by connecting a and B by a straight line.
The first intersection point set divided by the intersection point set is set as a point set above a straight line, and the second intersection point set is set as a point set below a straight line, according to the ordinate size of the intersection point in the intersection point sets.
And c3, ordering the intersection points in the first intersection point set and the second intersection point set based on the intersection point coordinates to obtain a third intersection point set and a fourth intersection point set.
And ordering the intersection points in the first intersection point set and the intersection points in the second intersection point set according to the order of the abscissa from large to small, wherein the ordered intersection point sets are a third intersection point set and a fourth intersection point set. The third intersection set is an intersection set after the first intersection set is ordered, and the fourth intersection set is an intersection set after the second intersection set is ordered.
Illustratively, as shown in fig. 4 (b), the intersections in the first set of intersections and the intersections in the second set of intersections are ordered by X-coordinates.
And c4, combining the third intersection point set and the fourth intersection point set to obtain the contour line sequence arrangement point set of each height.
After the third intersection point set and the fourth intersection point set of each height are obtained, merging intersection points in the third intersection point set and intersection points in the fourth intersection point set in reverse order to obtain a contour line sequence arrangement point set of each height.
And c5, sequentially arranging the intersection points in the point set according to the profile line sequence of each height, and connecting the intersection points to obtain the profile line of each height.
After the contour line sequence point set of each height is obtained, the intersection points of each height are connected according to the sequence of the intersection points in the point set, and the contour line of each height is obtained.
Illustratively, as shown in fig. 4 (c), the intersections are connected in the order of the third intersection set and the fourth intersection set in reverse order, to obtain the contour line.
And step S204, performing reverse modeling based on contour lines of all heights to obtain a solid model of the target object.
Please refer to step S104 in the embodiment shown in fig. 1 in detail, which is not described herein.
Illustratively, as shown in fig. 5 (a), a schematic diagram of a contour line is obtained for the helmet by performing linear fitting using the reverse modeling method of the present embodiment. And (3) performing reverse modeling based on the contour lines of all the heights of the safety helmet to obtain a physical model of the safety helmet shown in (b) in fig. 5.
As shown in fig. 6 (a), a schematic diagram of a three-dimensional point cloud model of a welded eccentric reducer is obtained by modeling the welded eccentric reducer using the reverse modeling method of the present embodiment, and then obtaining a solid model of the welded eccentric reducer as shown in fig. 6 (b).
Therefore, the reverse modeling method of the embodiment realizes automatic reverse modeling of all the target three-dimensional point cloud models.
According to the reverse modeling method provided by the embodiment, the contour point clouds of different heights of the target object in the normal direction are obtained by slicing the target three-dimensional point cloud model, the contour point clouds of each height are linearly fitted to obtain the contour line of each height, and the reverse modeling is performed based on the contour lines of all heights, so that the automatic reverse modeling of all the target objects is realized, and compared with the manual reverse modeling, the reverse modeling method provided by the embodiment is short in time consumption and high in efficiency.
In some alternative embodiments, determining the normal direction of the target object by:
Step d1, obtaining the core dimension of the target object, and determining the core dimension as the normal direction.
The core dimension is the dimension with the longest dimension length in the target object.
It should be noted that, in the three dimensions of the target object, the length of one dimension is significantly greater than the length of the other two dimensions, which are referred to as the core dimension of the target object, and the core dimension is the normal direction.
In an alternative embodiment, the method further comprises:
And importing the solid model of the target object into a Revit family library.
The entity model created by reverse modeling of the target three-dimensional point cloud model has no information of surface materials, truly reflects the information of the target three-dimensional point cloud model, can endow the model with materials, relevant performance attributes and other information, and can be edited in a Revit by a user or can be modified and perfected secondarily.
Among them, revit is the most commonly used software for building a BIM model.
In this embodiment, a reverse modeling apparatus is further provided, and the apparatus is used to implement the foregoing embodiments and preferred embodiments, and will not be described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The present embodiment provides a reverse modeling apparatus, as shown in fig. 7, including:
the target three-dimensional point cloud model acquisition module 701 is configured to acquire a target three-dimensional point cloud model of a target object.
The contour point cloud obtaining module 702 is configured to perform slicing processing on the target three-dimensional point cloud model to obtain contour point clouds of different heights of the target object in a normal direction, where the normal direction is any dimension direction predefined based on the target object.
The contour line obtaining module 703 is configured to perform linear fitting on the contour point cloud of each height, and obtain a contour line of each height.
The solid model obtaining module 704 is configured to perform inverse modeling based on contour lines of all heights, so as to obtain a solid model of the target object.
In some alternative embodiments, the contour point cloud acquisition module 702 includes:
And the tangent plane determining unit is used for determining a tangent plane of the target three-dimensional point cloud model, and the tangent plane is perpendicular to the normal direction.
The first contour point cloud acquisition subunit is used for carrying out slicing processing on the target three-dimensional point cloud model based on the tangent plane to obtain contour point clouds of different heights of the target object in the normal direction.
In some alternative embodiments, the contour line acquisition module 703 includes:
The contour point cloud dividing unit is used for dividing the contour point cloud of each height into an upper layer point cloud and a lower layer point cloud by taking the middle surface of the contour point cloud of each height as a reference surface.
And the point cloud pairing unit is used for pairing the upper point cloud and the lower point cloud of each height one by taking the shortest Euclidean distance as a searching target, and connecting the paired upper point cloud and lower point cloud by utilizing a straight line.
And the intersection set acquisition unit is used for acquiring the intersection set of each height straight line and the reference plane.
And the contour line acquisition subunit is used for connecting the intersection points in the intersection point set of each height to obtain the contour line of each height.
In some alternative embodiments, the tangent plane determination unit comprises:
And a contour point cloud thickness determination unit configured to determine a thickness of the contour point cloud, which is a thickness in the normal direction, based on the point cloud density.
And a tangent plane number determining unit for determining the number of tangent planes of the target three-dimensional point cloud model based on the thickness of the contour point cloud.
In some alternative embodiments, the contour point cloud acquisition module 702 includes:
and the second contour point cloud acquisition subunit is used for slicing the target three-dimensional point cloud model based on the thickness of the contour point cloud and the number of tangential planes to obtain contour point clouds of different heights of the target object in the normal direction.
In some alternative embodiments, the contour line acquisition subunit includes:
And the intersection point determining unit is used for determining a first intersection point and a second intersection point in each height intersection point set based on the intersection point coordinates, wherein the first intersection point is the intersection point with the largest intersection point X coordinate in each height intersection point set, and the second intersection point is the intersection point with the smallest intersection point X coordinate in each height intersection point set.
And the first intersection point connecting unit is used for connecting the first intersection point and the second intersection point by utilizing a straight line and dividing the intersection point in each height intersection point set into a first intersection point set and a second intersection point set.
And the intersection ordering unit is used for ordering the intersections in the first intersection set and the second intersection set based on the intersection coordinates to obtain a third intersection set and a fourth intersection set.
And the intersection point merging unit is used for merging the third intersection point set and the fourth intersection point set to obtain contour line sequence arrangement point sets of each height.
And the second intersection point connecting unit is used for connecting the intersection points according to the sequence of the intersection points in the point set arranged in the sequence of the contour lines of each height, so as to obtain the contour lines of each height.
In some alternative embodiments, an apparatus comprises:
the normal direction determining module is used for acquiring the core dimension of the target object and determining that the core dimension is the normal direction, wherein the core dimension is the dimension with the longest dimension length in the target object.
In some alternative embodiments, the target three-dimensional point cloud model acquisition module 701 includes:
The three-dimensional point cloud model acquisition unit is used for acquiring a three-dimensional point cloud model of the target object through a three-dimensional laser scanning technology.
The target three-dimensional point cloud model acquisition subunit is used for preprocessing the three-dimensional point cloud model to obtain a target three-dimensional point cloud model.
Further functional descriptions of the above respective modules and units are the same as those of the above corresponding embodiments, and are not repeated here.
The reverse modeling apparatus in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application SPECIFIC INTEGRATED Circuit) Circuit, a processor and a memory that execute one or more software or firmware programs, and/or other devices that can provide the above-described functions.
The embodiment of the invention also provides computer equipment, which is provided with the reverse modeling device shown in the figure 7.
Referring to fig. 8, fig. 8 is a schematic structural diagram of a computer device according to an alternative embodiment of the present invention, as shown in fig. 8, the computer device includes: one or more processors 801, memory 802, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The various components are communicatively coupled to each other using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the computer device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In some alternative embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple computer devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 801 is illustrated in fig. 8.
The processor 801 may be a central processor, a network processor, or a combination thereof. The processor 801 may further include a hardware chip, among others. The hardware chip may be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general-purpose array logic, or any combination thereof.
Wherein the memory 802 stores instructions executable by the at least one processor 801 to cause the at least one processor 801 to perform the methods shown to implement the above embodiments.
Memory 802 may include a storage program area that may store an operating system, at least one application program required for functionality, and a storage data area; the storage data area may store data created according to the use of the computer device, etc. In addition, memory 802 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 802 may optionally include memory located remotely from processor 801, which may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Memory 802 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk, or solid state disk; memory 802 may also include combinations of the above types of memory.
The computer device also includes a communication interface 803 for the computer device to communicate with other devices or communication networks.
The embodiments of the present invention also provide a computer readable storage medium, and the method according to the embodiments of the present invention described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk or the like; further, the storage medium may also comprise a combination of memories of the kind described above. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (10)
1.A method of reverse modeling, the method comprising:
Acquiring a target three-dimensional point cloud model of a target object;
Slicing the target three-dimensional point cloud model to obtain contour point clouds of different heights of the target object in the normal direction, wherein the normal direction is any one dimension direction predefined based on the target object;
Linearly fitting the contour point cloud of each height to obtain a contour line of each height;
and (5) carrying out reverse modeling based on contour lines of all heights to obtain a solid model of the target object.
2. The method according to claim 1, wherein slicing the target three-dimensional point cloud model to obtain contour point clouds of different heights of the target object in a normal direction comprises:
Determining a tangential plane of the target three-dimensional point cloud model, wherein the tangential plane is perpendicular to the normal direction;
And slicing the target three-dimensional point cloud model based on the slicing plane to obtain contour point clouds with different heights of the target object in the normal direction.
3. The method of claim 1, wherein the linearly fitting the contour point cloud for each height to obtain the contour line for each height comprises:
Dividing the outline point cloud of each height into an upper layer point cloud and a lower layer point cloud by taking the middle surface of the outline point cloud of each height as a reference surface;
The shortest Euclidean distance is used as a searching target, the upper layer point cloud and the lower layer point cloud of each height are paired one by one, and the paired upper layer point cloud and lower layer point cloud are connected by utilizing a straight line;
acquiring a set of intersections of the straight lines and the reference surface at each height;
And connecting the intersection points in the intersection point set of each height to obtain the contour line of each height.
4. The method of claim 2, wherein the determining a tangent plane of the target three-dimensional point cloud model comprises:
Determining the thickness of the contour point cloud based on the point cloud density, wherein the thickness is the thickness in the normal direction;
Determining the number of tangential planes of the target three-dimensional point cloud model based on the thickness of the contour point cloud;
The slicing processing is performed on the target three-dimensional point cloud model based on the slicing plane to obtain contour point clouds of different heights of the target object in the normal direction, including:
And slicing the target three-dimensional point cloud model based on the thickness of the contour point cloud and the number of tangential planes to obtain contour point clouds with different heights of the target object in the normal direction.
5. A method according to claim 3, wherein said connecting the intersections in the set of intersections for each height to obtain the contour line for each height comprises:
Determining a first intersection point and a second intersection point in the intersection point set of each height based on the intersection point coordinates, wherein the first intersection point is an intersection point with the largest intersection point X coordinate in the intersection point set of each height, and the second intersection point is an intersection point with the smallest intersection point X coordinate in the intersection point set of each height;
The first intersection point and the second intersection point are connected through a straight line, and the intersection point set of each height is divided into a first intersection point set and a second intersection point set;
Ordering the intersection points in the first intersection point set and the second intersection point set based on the intersection point coordinates to obtain a third intersection point set and a fourth intersection point set;
combining the third intersection point set and the fourth intersection point set to obtain contour line sequence arrangement point sets of each height;
and connecting the intersection points according to the sequence of the intersection points in the point set arranged in the sequence of the contour lines of each height, and obtaining the contour lines of each height.
6. The method according to claim 1, wherein determining the normal direction of the target object by:
And acquiring a core dimension of the target object, and determining the core dimension as a normal direction, wherein the core dimension is the dimension with the longest dimension length in the target object.
7. The method of claim 1, wherein the obtaining a target three-dimensional point cloud model of the target object comprises:
Acquiring a three-dimensional point cloud model of a target object through a three-dimensional laser scanning technology;
And preprocessing the three-dimensional point cloud model to obtain a target three-dimensional point cloud model.
8. A reverse modeling apparatus, the apparatus comprising:
the target three-dimensional point cloud model acquisition module is used for acquiring a target three-dimensional point cloud model of a target object;
The contour point cloud acquisition module is used for carrying out slicing processing on the target three-dimensional point cloud model to obtain contour point clouds with different heights of the target object in the normal direction, wherein the normal direction is any one dimension direction predefined based on the target object;
The contour line acquisition module is used for carrying out linear fitting on the contour point cloud of each height to obtain a contour line of each height;
And the solid model acquisition module is used for carrying out reverse modeling based on the contour lines of all the heights to obtain a solid model of the target object.
9. A computer device, comprising:
a memory and a processor in communication with each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the reverse modeling method of any of claims 1-7.
10. A computer-readable storage medium having stored thereon computer instructions for causing a computer to perform the reverse modeling method of any of claims 1 to 7.
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