LOD model simplification method for constructing a three-dimensional model and related apparatus

Abstract

The application discloses a LOD model simplification method for constructing a three-dimensional model and a related device. The method comprises the following steps: constructing a multi-level LOD model of a three-dimensional model according to image data; and simplifying the multi-level LOD model based on a preset scaling level and an edge recognition result of a main structure in the multi-level LOD model, wherein the edge recognition result of the main structure at least comprises edge bodies, and a plurality of the edge bodies are formed by each independent grid set with complete edges. The application solves the technical problem of affecting the model structure in the process of model simplification and compression. Through the simplification method, the main structure after model simplification can be well maintained in the case of ensuring that the model is simplified and compressed.

Description

Technical Field

[0001] This application relates to the fields of computer software and image processing, and more specifically, to a method and apparatus for simplifying LOD models for constructing 3D models. Background Technology

[0002] The LOD model can determine the resource allocation for object rendering based on the position and importance of the object model's nodes in the display environment, reducing the face count and detail of unimportant objects, thereby achieving high-efficiency rendering.

[0003] The simplification process for different levels of models can damage the model's structure, leading to severe deformation of the model structure when the simplification ratio is large.

[0004] There is currently no effective solution to the problem of model simplification and compression affecting model structure in related technologies. Summary of the Invention

[0005] The main objective of this application is to provide a method and related apparatus for simplifying LOD models used in constructing 3D models, so as to solve the problem of affecting the model structure during the model simplification and compression process.

[0006] To achieve the above objectives, according to one aspect of this application, a method for simplifying LOD models for constructing three-dimensional models is provided.

[0007] The method for simplifying a LOD model for constructing a 3D model according to this application includes: constructing a multi-level LOD model of the 3D model based on image data; simplifying the multi-level LOD model based on a preset scaling level and the edge recognition results of the main structure in the multi-level LOD model, wherein the edge recognition results of the main structure include at least edge volumes, and multiple edge volumes are composed of each independent set of grids with complete edges.

[0008] Furthermore, the simplification of the multi-level LOD model based on the preset scaling level and the edge recognition results of the main structure in the multi-level LOD model also includes: simplifying the multi-level LOD model while keeping the main structure in the multi-level LOD model at its original size according to the edge recognition results.

[0009] Furthermore, the simplification of the multi-level LOD model based on the preset scaling level and the edge recognition results of the main structure in the multi-level LOD model also includes: during the simplification of the multi-level LOD model, while simplifying the structure inside the edge body, ensuring that the edges on the edge of the edge body are not simplified, wherein the structural simplification inside the edge body is a simplification process performed according to different proportions.

[0010] Further, the simplifying the multi-level LOD model based on the preset scaling level and the edge recognition result of the main structure in the multi-level LOD model further comprises: performing texture simplification in the edge body during the simplifying process of the multi-level LOD model, wherein the texture inside the edge body is reduced in proportion.

[0011] Further, the edge recognition result of the main structure in the multi-level LOD model is obtained by: performing processing on the texture map of the three-dimensional model according to different blocks based on a preset texture processing method, and positioning the edge of the main structure based on the block texture map.

[0012] Further, the edge recognition result of the main structure in the multi-level LOD model is obtained by: determining an arbitrary grid as a target grid in the image data based on a preset normal processing method; and obtaining a plurality of grid sets with complete edges by calculating the normal relationship between the peripheral grid of the target grid and the target grid and continuously expanding the range of the grid.

[0013] Further, after the simplifying the multi-level LOD model based on the preset scaling level and the edge recognition result of the main structure in the multi-level LOD model, the method further comprises: adjusting the fineness of the multi-level LOD model according to the simplification result of the multi-level LOD model at different viewing angles and / or viewing distances.

[0014] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a device for simplifying the LOD model of a three-dimensional model is provided.

[0015] The device for simplifying the LOD model of a three-dimensional model according to the present application comprises: a multi-level LOD module for constructing a multi-level LOD model of a three-dimensional model according to image data; and a simplification module for simplifying the multi-level LOD model based on a preset scaling level and an edge recognition result of a main structure in the multi-level LOD model, wherein the edge recognition result of the main structure at least comprises an edge body, and a plurality of the edge bodies are formed by each independent grid set with complete edges.

[0016] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a storage medium is also provided, and the storage medium stores a computer program, wherein the computer program is set to execute the steps in any one of the method embodiments when running.

[0017] To achieve the above object, according to another aspect of the present application, there is also provided an electronic device comprising a memory and a processor, the memory storing a computer program, and the processor being configured to run the computer program to perform the steps in any of the method embodiments.

[0018] The LOD model simplification method for constructing a three-dimensional model and the related device in the embodiments of the present application adopt a multi-level LOD model for constructing a three-dimensional model according to image data, and simplify the multi-level LOD model based on a preset scaling level and an edge recognition result of a main structure in the multi-level LOD model, so as to improve the compression and simplification performance of the LOD model, thereby achieving the technical effect that the main structure after model simplification can be well maintained in the case of guaranteeing that the model is simplified and compressed, and further solving the technical problem of affecting the model structure in the process of model simplification and compression. BRIEF DESCRIPTION OF DRAWINGS

[0019] The accompanying drawings, which form a part of this application, are intended to provide further understanding of the application and are incorporated herein for a purpose of explanations and are in no way limiting to the present application. The schematic embodiment drawings of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation to the present application. In the drawings:

[0020] Figure 1 is a hardware structure schematic diagram of the LOD model simplification method for constructing a three-dimensional model according to the embodiments of the present application;

[0021] Figure 2 is a flowchart schematic diagram of the LOD model simplification method for constructing a three-dimensional model according to the embodiments of the present application;

[0022] Figure 3 is a hardware structure schematic diagram of the LOD model simplification device for constructing a three-dimensional model according to the embodiments of the present application;

[0023] Figure 4 is a texture division schematic diagram in the LOD model simplification method for constructing a three-dimensional model according to the embodiments of the present application;

[0024] Figure 5 is an implementation principle schematic diagram of the LOD model simplification method for constructing a three-dimensional model according to the embodiments of the present application. DETAILED DESCRIPTION

[0025] In order to make the personnel in the technical field better understand the scheme of the present application, the technical scheme in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor should belong to the scope of protection of the present application.

[0026] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0027] In the present application, the terms "upper", "lower", "left", "right", "front", "back", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate the orientation or positional relationship shown in the drawings. These terms are mainly used to better describe the present application and its embodiments, and are not intended to limit the indicated devices, elements or components to have a specific orientation, or to be constructed and operated in a specific orientation.

[0028] In addition, in addition to indicating the orientation or positional relationship, the above-mentioned part of the terms can also be used to indicate other meanings, for example, the term "upper" can also be used to indicate a certain dependent relationship or connection relationship in some cases. For those of ordinary skill in the art, the specific meaning of these terms in the present application can be understood according to the specific circumstances.

[0029] In addition, the terms "mount", "set", "provided with", "connected", "connected", "sleeved" should be broadly understood. For example, it can be fixedly connected, detachably connected, or integrally constructed; it can be mechanically connected, or electrically connected; it can be directly connected, or indirectly connected through an intermediate medium, or internal communication between two devices, elements or components. For those of ordinary skill in the art, the specific meaning of the above-mentioned terms in the present application can be understood according to the specific circumstances.

[0030] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0031] like Figure 1 The diagram shows the hardware structure in an embodiment of this application. The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking its operation on a mobile terminal as an example... Figure 1 This is a hardware structure block diagram of a mobile terminal for a method of simplifying LOD models for constructing 3D models, according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal 10 may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. Optionally, the mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal 10 may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0032] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the signal processing method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0033] The transmission device 106 is configured to receive or send data via a network. The network can include a wireless network provided by a communication provider of the mobile terminal 10. In one embodiment, the transmission device 106 includes a network interface controller (NIC) configured to connect to other network devices via a base station to communicate with the Internet. In one embodiment, the transmission device 106 can be a radio frequency (RF) module configured to communicate with the Internet via a wireless network.

[0034] As shown in Figure 2 The method includes the following steps S201 to S202:

[0035] In step S201, a multi-level LOD model of a three-dimensional model is constructed according to image data.

[0036] In step S202, the multi-level LOD model is simplified based on a preset zoom level and an edge recognition result of a main structure in the multi-level LOD model, wherein the edge recognition result of the main structure at least includes edge bodies, and the edge bodies are formed by each independent grid set having complete edges.

[0037] From the above description, it can be seen that the present application achieves the following technical effects:

[0038] By constructing a multi-level LOD model of a three-dimensional model according to image data, and simplifying the multi-level LOD model based on a preset zoom level and an edge recognition result of a main structure in the multi-level LOD model, the compression and simplification performance of the LOD model is improved, so that the main structure of the model after simplification can be well maintained, thereby solving the technical problem of affecting the model structure during model simplification and compression.

[0039] In step S201, a multi-level LOD model of a three-dimensional model is constructed according to image data. For example, a multi-level LOD model of a three-dimensional model is constructed based on image data. It should be noted that during the construction of the multi-level LOD model of the three-dimensional model, the model is simplified according to different zoom levels, so that the model precision is different under different viewing angles and viewing distances, and further guaranteeing the continuous user operation experience.

[0040] As an optional embodiment, the model compression and model simplification are further performed based on the multi-level LOD model.

[0041] As an optional implementation, in the simplification process for different level models, the structure of the model is as little as possible to be damaged. For example, if the simplification ratio is large, the model structure needs to be prevented from being deformed.

[0042] In step S202, the multi-level LOD model is simplified based on the preset scaling level and the edge recognition result of the main structure in the multi-level LOD model. It can be understood that the preset scaling level can be the scaling ratio of the map data or the scaling ratio of the target data. The main structure in the multi-level LOD model refers to the main structure in three-dimensional modeling. The main structure contains edges, and the edges of the main structure need to be identified.

[0043] As an optional implementation, the edge recognition result of the main structure at least includes an edge body.

[0044] As an optional implementation, a plurality of edge bodies are formed by a grid set that independently has complete edges. It can be understood that the grid set refers to a plurality of grids obtained after edge recognition.

[0045] Preferably, after the multi-level LOD model is simplified based on the preset scaling level and the edge recognition result of the main structure in the multi-level LOD model, the method further comprises: adjusting the fineness of the multi-level LOD model at different viewing angles and / or viewing distances according to the simplification result of the multi-level LOD model.

[0046] As a preferred embodiment in the present embodiment, the multi-level LOD model is simplified based on the preset scaling level and the edge recognition result of the main structure in the multi-level LOD model, and further comprises: maintaining the main structure in the multi-level LOD model as the original size while simplifying the multi-level LOD model according to the edge recognition result.

[0047] In specific implementation, when the multi-level LOD model is simplified, the main structure in the multi-level LOD model needs to be maintained as the original size while the multi-level LOD model is simplified according to the edge recognition result. The edge body outline obtained according to the edge recognition result can maintain the main structure in the multi-level LOD model as the original size while simplifying the structure. For example, when the map scaling level changes from L20 to L17, the triangular patches in the simplified image need to be prevented from being damaged. According to the edge recognition result, the edges are identified and locked to ensure that the edges will not be compressed. That is, the outer contour of the main structure is determined, and the inside can be simplified.

[0048] As preferred in the embodiment, the multi-level LOD model is simplified based on the preset scaling level and the edge recognition result of the main structure in the multi-level LOD model, wherein the edge recognition result of the main structure at least includes an edge body, and a plurality of the edge bodies are formed by each independent grid set with complete edges, and the structure simplification is performed inside the edge body while ensuring that the edges on the edge of the edge body are not simplified in the process of simplifying the multi-level LOD model, and the structure simplification inside the edge body is performed in different proportions.

[0049] In implementation, the edge body is constructed, and each independent grid set with complete edges forms an edge body according to the edge recognition result. The structure simplification is performed inside the edge body while ensuring that the edges on the edge of the edge body are not simplified, so that the stability of the main structure of the model is ensured, and the structure inside the edge body is simplified in different proportions, effectively reducing the size of the structure.

[0050] As preferred in the embodiment, the multi-level LOD model is simplified based on the preset scaling level and the edge recognition result of the main structure in the multi-level LOD model, wherein the edge recognition result of the main structure at least includes an edge body, and a plurality of the edge bodies are formed by each independent grid set with complete edges, and the texture simplification is performed inside the edge body in the process of simplifying the multi-level LOD model, and the texture inside the edge body is processed in different proportions.

[0051] In implementation, the structure simplification is performed inside the edge body while ensuring that the edges on the edge of the edge body are not simplified, so that the stability of the main structure of the model is ensured, and the structure inside the edge body is simplified in different proportions, effectively reducing the size of the structure. Further, the texture simplification is performed inside the edge body, and the texture inside the edge body is processed, and the problem inside the edge body is processed in different proportions.

[0052] As preferred in the embodiment, the edge recognition result of the main structure in the multi-level LOD model is obtained by: performing processing on the texture map of the three-dimensional model in different blocks based on a preset texture processing method, and positioning the edge of the main structure based on the blocked texture map.

[0053] In implementation, the texture-based method is used, and the texture map of the three-dimensional model is processed in blocks, as shown in FIG. 4. Figure 4 The gray line in the figure depicts the texture boundary, so the blocked texture map can be used to position the edge of the main structure.

[0054] As preferred in the embodiment, the edge recognition result of the main structure in the multi-level LOD model is obtained by: determining an arbitrary grid as a target grid in the image data based on a preset normal processing method; and obtaining a plurality of grid sets with complete edges by calculating the normal relationship between the peripheral grids and the target grid and continuously expanding the range of the grid.

[0055] In implementation, the normal-based method selects a grid, continuously expands the range of the grid by calculating the normal relationship between the peripheral grids and the target grid, and forms a plurality of grid sets with complete edges until the expansion ends and no further expansion is possible.

[0056] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed 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 herein can be executed in an order different from that shown.

[0057] According to the embodiments of the present application, a LOD model simplification device for constructing a three-dimensional model is also provided for implementing the above method, as shown in Figure 3 The device comprises:

[0058] A multi-level LOD module 301 is configured to construct a multi-level LOD model of a three-dimensional model according to image data.

[0059] A simplification module 302 is configured to simplify the multi-level LOD model based on a preset scaling level and an edge recognition result of a main structure in the multi-level LOD model, wherein the edge recognition result of the main structure at least includes edge bodies, and a plurality of the edge bodies are formed by each independent grid set with complete edges.

[0060] The multi-level LOD module 301 constructs a multi-level LOD model of a three-dimensional model according to the obtained image data. For example, a multi-level LOD model of a three-dimensional model needs to be constructed based on image data. It should be noted that in the process of constructing a multi-level LOD model of a three-dimensional model, the model is simplified according to different scaling levels, so that the model has different levels of detail under different viewing angles and distances, and further guarantees the continuous user operation experience.

[0061] As an optional implementation, the model compression and model simplification are further performed based on the multi-level LOD model.

[0062] As an optional implementation, in the process of simplifying different level models, the structure of the model is as little damaged as possible. For example, if the simplification ratio is large, the possible deformation of the model structure needs to be prevented.

[0063] The simplification module 302 simplifies the multi-level LOD model based on the preset scaling level and the edge recognition result of the main structure in the multi-level LOD model. It can be understood that the preset scaling level can be a scaling ratio of the map data or a scaling ratio of the target data. The main structure in the multi-level LOD model refers to a main structure in three-dimensional modeling. The main structure contains edges, and the edges of the main structure need to be recognized.

[0064] As an optional implementation, the edge recognition result of the main structure at least includes an edge body.

[0065] As an optional implementation, the plurality of edge bodies are formed by a plurality of grid sets each independently having complete edges. It can be understood that the grid set refers to a plurality of grids obtained after edge recognition.

[0066] Obviously, those skilled in the art should understand that the modules or steps of the present application described above can be realized by a general computing device, which can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. Alternatively, they can be realized by program codes executable by a computing device, so that they can be stored in a storage device and executed by a computing device, or they can be respectively manufactured into individual integrated circuit modules, or a plurality of modules or steps among them can be manufactured into a single integrated circuit module. Thus, the present application is not limited to any specific combination of hardware and software.

[0067] In order to better understand the above method for simplifying the LOD model for constructing a three-dimensional model, the above technical solutions will be explained in combination with the preferred embodiments, but not used to limit the technical solutions of the embodiments of the present application.

[0068] The method in the embodiments of the present application achieves the technical effect that the main structure after model simplification can be well maintained in the case of ensuring that the model is simplified and compressed, thereby solving the technical problem of affecting the model structure in the process of model simplification and compression.

[0069] As shown in Figure 5 Fig. 1 is a flowchart of a method for simplifying an LOD model for constructing a three-dimensional model according to an embodiment of the present application, and specifically includes the following steps:

[0070] Step S501, constructing a multi-level LOD model of a three-dimensional model according to image data.

[0071] In step S502, the multi-level LOD model is simplified based on the preset scaling level and the edge identification result of the main structure in the multi-level LOD model, wherein the edge identification result of the main structure at least includes edge bodies, and the edge bodies are formed by each independent grid set with complete edges.

[0072] In step S503, the main structure in the multi-level LOD model is kept in the original size according to the edge identification result, and the multi-level LOD model is simplified.

[0073] In step S504, in the process of simplifying the multi-level LOD model, the structure inside the edge body is simplified while ensuring that the edges on the edge body are not simplified, wherein the structure inside the edge body is simplified in different proportions.

[0074] In step S505, in the process of simplifying the multi-level LOD model, the texture inside the edge body is simplified, wherein the texture inside the edge body is reduced in proportion.

[0075] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Those skilled in the art can make various modifications and changes to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A LOD model simplification method for constructing a three-dimensional model, characterized in that, The method comprises the following steps: constructing a multi-level LOD model of a three-dimensional model according to image data; simplifying the multi-level LOD model based on a preset zoom level and edge recognition results of a main structure in the multi-level LOD model, wherein the edge recognition results of the main structure at least include edge bodies, and a plurality of the edge bodies are formed by each independent grid set with complete edges; the simplifying the multi-level LOD model based on the preset zoom level and the edge recognition results of the main structure in the multi-level LOD model further comprises: maintaining the main structure in the multi-level LOD model as an original size while simplifying the multi-level LOD model according to the edge recognition results; in the process of simplifying the multi-level LOD model, structure simplification is performed inside the edge bodies while ensuring that edges on edges of the edge bodies are not simplified, wherein the structure simplification performed inside the edge bodies is simplification processing in different proportions; in the process of simplifying the multi-level LOD model, texture simplification is performed inside the edge bodies, wherein the texture inside the edge bodies is proportionally reduced in blocks; the edge recognition results of the main structure in the multi-level LOD model are obtained by the following method: processing texture maps of the three-dimensional model in different blocks based on a preset texture processing method, and positioning edges of the main structure based on the block texture maps; determining any grid as a target grid in the image data based on a preset normal processing method; obtaining a plurality of grid sets with complete edges by calculating the relationship between the peripheral grids of the target grid and the normal of the target grid, and continuously expanding the range of the grid; after the simplifying the multi-level LOD model based on the preset zoom level and the edge recognition results of the main structure in the multi-level LOD model, the method further comprises: adjusting the fineness of the multi-level LOD model at different viewing angles and / or viewing distances according to the simplification results of the multi-level LOD model.

2. An LOD model simplification apparatus for constructing a three-dimensional model, characterized by, The method comprises the following steps: a multi-level LOD module for constructing a multi-level LOD model of a three-dimensional model according to image data; a simplification module for simplifying the multi-level LOD model based on a preset zoom level and edge recognition results of a main structure in the multi-level LOD model, wherein the edge recognition results of the main structure at least include edge bodies, and a plurality of the edge bodies are formed by each independent grid set with complete edges; the simplifying the multi-level LOD model based on the preset zoom level and the edge recognition results of the main structure in the multi-level LOD model further comprises: maintaining the main structure in the multi-level LOD model as an original size while simplifying the multi-level LOD model according to the edge recognition results; in the process of simplifying the multi-level LOD model, structure simplification is performed inside the edge bodies while ensuring that edges on edges of the edge bodies are not simplified, wherein the structure simplification performed inside the edge bodies is simplification processing in different proportions; In the process of simplifying the multi-level LOD model, texture simplification is performed inside the edge body, wherein the texture inside the edge body is scaled in a whole block manner; The edge recognition result of the main structure in the multi-level LOD model is obtained by: Processing the texture map of the three-dimensional model according to different blocks based on a preset texture processing method, and positioning the edge of the main structure based on the texture map in blocks; Determining any grid as a target grid in the image data based on a preset normal processing method; Obtaining a plurality of grid sets with complete edges by calculating the normal relationship between the peripheral grid of the target grid and the target grid and continuously expanding the range of the grid; After the multi-level LOD model is simplified based on the preset scaling level and the edge recognition result of the main structure in the multi-level LOD model, the method further comprises: Adjusting the fineness of the multi-level LOD model at different viewing angles and / or viewing distances according to the simplification result of the multi-level LOD model.

3. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, wherein the computer program is configured to execute the method of claim 1 when running. 4.An electronic device comprising a memory and a processor, the electronic device characterized by, The memory stores a computer program, and the processor is configured to execute the computer program to execute the method of claim 1.

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