Design material management system and related devices based on 3D object customization

Abstract

The present invention discloses a design material management system based on 3D object customization and related devices, wherein the system includes: a material collection module; a material retrieval module, including a semantic retrieval submodule, a component retrieval submodule, and a model retrieval submodule, for searching a material library and / or collecting materials based on input sentences, images, or 3D models, to obtain material statistical information and material combination information; wherein the material statistical information includes the number of times a material is used, the number of times a material is edited, and the number of times a material is combined, and the material combination information includes the associated components and associated 3D models of the material; a material design module for editing and integrating selected materials into the 3D object customization model; and a material storage module for storing edited materials and integrated 3D object models in the material design module. The present invention integrates a material management system into the 3D object customization model, performs associated retrieval and storage of materials, and improves the efficiency of material management and 3D object design.

Description

Technical Field

[0001] The present invention relates to the field of 3D object customization and automated office technology, and in particular to a design material management system based on 3D object customization and related devices. Background Art

[0002] Personalized items are becoming increasingly sought-after and popular products, including packaging (such as cigarette boxes and gift boxes), wooden products, metal products, ceramics, and glass products. Personalized customization can also boost corporate brands and product sales. To enrich and improve the models of customized items, designers need to pre-design some 3D objects and embed them into the item customization model for users to select and edit.

[0003] Designers need a large amount of design materials when designing 3D object models. Searching for materials on the Internet is time-consuming and laborious, the retrieval format is single, and it is difficult to retrieve accurate materials and related components, related 3D models, etc. Edited materials and integrated 3D object models are not effectively stored and reused, resulting in problems such as irregular material management and low 3D object design efficiency.

[0004] Therefore, the issue of how to highly integrate the material management system into the customized 3D object model needs to be solved urgently. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a design material management system and computing device based on 3D object customization that overcome the above problems of irregular design material management and low design efficiency based on 3D object customization.

[0006] According to one aspect of the present invention, a design material management system based on 3D object customization is provided, comprising:

[0007] Material collection module, including design material uploading submodule, design material collection submodule and design material scanning submodule;

[0008] A material retrieval module, comprising a semantic retrieval submodule, a component retrieval submodule, and a model retrieval submodule, is configured to retrieve a material library and / or collect materials based on input sentences, images, or 3D models, and obtain material statistics and material combination information; wherein the material statistics include the number of times a material has been used, the number of times a material has been edited, and the number of times a material has been combined; and the material combination information includes the associated components and associated 3D models of the material;

[0009] The material design module is used to edit and integrate the selected materials into the customized 3D object model, generate public and private keys based on an asymmetric encryption key generation algorithm, and encrypt the edited materials corresponding to the selected materials and the integrated 3D object model using the private key set by the designer;

[0010] The material storage module is used to store the material information collected by the material collection module, and to store the edited materials and integrated 3D object models in the material design module.

[0011] In an optional manner, after or while encrypting the edited material and the integrated 3D object model corresponding to the selected material using the private key set by the designer, the material design module further includes:

[0012] An encryption period is set for the edited material and the integrated 3D object model, and the edited material and the integrated 3D object model are automatically decrypted after the encryption period is reached.

[0013] In an optional manner, the component retrieval submodule and the model retrieval submodule further include:

[0014] The DBSCAN clustering algorithm is used to perform cluster analysis on the 3D coordinates of the part or model to be retrieved and the 3D coordinates in the material library to obtain materials similar to the part or model to be retrieved.

[0015] In an optional manner, the component retrieval submodule and the model retrieval submodule further include:

[0016] Step S1, obtaining each view of the component or model to be retrieved;

[0017] Step S2: for any view of the component or model to be retrieved, calculate the 3D coordinate points of the view and the coordinates of each material view in the material library. Figure 3 A first minimum Manhattan distance of the D coordinate, when the first minimum Manhattan distance is less than a first preset threshold, a first search set is obtained;

[0018] Step S3, repeating step S2, respectively calculating the other views of the part or model to be retrieved and the material views in the first retrieval set. Figure 3 The second minimum Manhattan distance of the D coordinate is obtained when the second minimum Manhattan distance is less than a second preset threshold.

[0019] In an optional manner, performing cluster analysis on the 3D coordinates of the part or model to be retrieved and the 3D coordinates in the material library using the DBSCAN clustering algorithm to obtain materials similar to the part or model to be retrieved further includes:

[0020] Step S1, using viewpoint entropy and view stability to select the optimal view of the part or model to be retrieved Figure 3 D coordinate;

[0021] Step S2: Gabor filter is used to filter the optimal view. Figure 3 The D coordinates are convolved to obtain the 3D feature coordinates of the optimal view;

[0022] Step S3: using the DBSCAN clustering algorithm to perform cluster analysis on the 3D feature coordinates of the optimal view and the 3D feature coordinates of the optimal view corresponding to each material in the material library, to obtain materials similar to the part or model to be retrieved.

[0023] In an optional manner, the material retrieval module further includes:

[0024] Step S1, pre-encode the materials in the material library and set a corresponding relationship table between the associated combined materials and material models;

[0025] Step S2, searching the material library for the corresponding combination material and material model according to the material code to be retrieved;

[0026] Step S3: sorting the combined materials and material models according to the information of the number of times the materials are used, the number of times the materials are edited, and the number of times the materials are combined.

[0027] In an optional manner, the material storage module further includes:

[0028] The collected material information, the edited material, and the integrated 3D object model are treated as new materials and indexed;

[0029] Specifically, first index information is created for the rendering, lighting, 3D coordinates, and size information of the newly added material;

[0030] Creating second index information for the newly added material and the same material in the material library;

[0031] A third index information is established for the name and name classification information of the newly added material.

[0032] In an optional manner, the semantic retrieval submodule further includes:

[0033] Step S1, inputting the sentence into the LDA topic model to generate a preset number of topics;

[0034] Step S2: for any LDA topic model, calculate the Euclidean distance of the topic distribution vector between the LDA subject model and each material in the material library, as well as the associated combined material and the material model;

[0035] Step S3: sorting by the Euclidean distance to obtain material statistical information and material combination information corresponding to the sentence.

[0036] In an optional manner, the material design module further includes:

[0037] In response to an editing operation on the 3D object model, obtaining a material selected in the 3D object model and displaying materials and material combination information similar to the material;

[0038] In response to a replacement operation on the material and the material combination information, the selected material in the 3D object model is replaced.

[0039] According to another aspect of the present invention, there is provided a computing device comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0040] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the above-mentioned design material management system based on 3D object customization.

[0041] The solution provided by the present invention includes: a material collection module, including a design material upload submodule, a design material acquisition submodule, and a design material scanning submodule; a material retrieval module, including a semantic retrieval submodule, a component retrieval submodule, and a model retrieval submodule, for searching a material library and / or collecting materials based on an input sentence, image, or 3D model, to obtain material statistical information and material combination information; wherein the material statistical information includes the number of times a material is used, the number of times a material is edited, and the number of times a material is combined, and the material combination information includes the associated components and associated 3D models of the material; a material design module, for editing and integrating selected materials into a customized 3D object model, generating a public key and a private key based on an asymmetric encryption key generation algorithm, and encrypting the edited materials corresponding to the selected materials and the integrated 3D object model using the private key set by the designer; and a material storage module, for storing the material information collected by the material collection module, and storing the edited materials and the integrated 3D object model in the material design module. The present invention integrates a material management system into the customized 3D object model to perform associated retrieval and storage of materials, thereby improving material management and 3D object design efficiency.

[0042] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0044] Figure 1 The structure of the design material management system based on 3D object customization according to an embodiment of the present invention is shown. Figure 1 ;

[0045] Figure 2 The structure of the design material management system based on 3D object customization according to an embodiment of the present invention is shown. Figure 2 ;

[0046] Figure 3 A schematic diagram showing the flow of a material retrieval module according to an embodiment of the present invention is shown;

[0047] Figure 4 A schematic diagram showing the flow of the semantic retrieval submodule of an embodiment of the present invention is shown;

[0048] Figure 5 A schematic diagram of a process for obtaining materials similar to a part or model to be retrieved according to an embodiment of the present invention is shown;

[0049] Figure 6 The material retrieval diagram of the embodiment of the present invention is shown Figure 1 ;

[0050] Figure 7 The material retrieval diagram of the embodiment of the present invention is shown Figure 2 ;

[0051] Figure 8 A schematic structural diagram of a computing device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0052] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0053] Figure 1 The structure of the design material management system based on 3D object customization according to an embodiment of the present invention is shown. Figure 1 This method integrates the material management system into the 3D object customization model to perform associated retrieval and storage of materials. Specifically, Figure 1 As shown, it includes material collection module, material retrieval module, material design module and material storage module:

[0054] Among them, the material collection module is used to collect various design materials and upload them to the system, including a design material uploading sub-module, a design material collection sub-module and a design material scanning sub-module. The design material collection sub-module connects to the material search engine to collect the required design materials from the Internet. The design material scanning sub-module is used to perform two-dimensional or three-dimensional scanning of image materials into 3D model format materials.

[0055] The material retrieval module includes a semantic retrieval submodule, a component retrieval submodule, and a model retrieval submodule, which is used to retrieve the material library and / or collect materials based on the input sentence, picture or 3D model to obtain material statistics information and material combination information. Figure 6 、 Figure 7 As shown, keyword / semantic search or image search is performed through the semantic retrieval submodule to obtain material statistical information (such as the number of times the material is edited and combined, etc.) and material combination information (such as the components of the material and the assembly model, etc.).

[0056] In this embodiment, the material statistical information includes the number of times the material is used, the number of times the material is edited, and the number of times the material is combined. The material combination information includes the associated components and associated 3D models of the material. Material designers can understand similar designs of materials through the material combination information.

[0057] The material design module is used to edit and integrate the selected materials in the customized 3D object model, generate public and private keys based on the asymmetric encryption key generation algorithm, and use the private key set by the designer to encrypt the edited materials corresponding to the selected materials and the integrated 3D object model. Figure 2As shown, the designer encrypts and stores the edited materials and the integrated 3D object model. The designer can use the public key to decrypt and use their own materials, which can protect the designer's copyright to the materials. For example, based on an asymmetric encryption key generation algorithm, a public key and a private key are generated, and the material information (such as the encoding of the material) is encrypted using the private key. The asymmetric encryption algorithm is used to generate a randomly generated key pair, namely a public key (K1) and a private key (K2). After the key pair is generated, the public key K1 is stored in the material library and used as the decryption key for the material information. The private key K2 is used as the encryption key. Based on the private key K2 in the key pair, the material D1 is encrypted using a common asymmetric encryption algorithm, such as RSA.

[0058] The material storage module is used to store the material information collected by the material collection module, and to store the edited materials and integrated 3D object models in the material design module.

[0059] In an optional manner, after or while encrypting the edited material and the integrated 3D object model corresponding to the selected material using the private key set by the designer, the material design module further includes:

[0060] An encryption period is set for the edited material and the integrated 3D object model, and the edited material and the integrated 3D object model are automatically decrypted after the encryption period is reached.

[0061] In an optional manner, the component retrieval submodule and the model retrieval submodule further include:

[0062] The DBSCAN clustering algorithm is used to perform cluster analysis on the 3D coordinates of the part or model being retrieved and the 3D coordinates in the material library to obtain materials similar to the part or model being retrieved. The DBSCAN clustering algorithm is an unsupervised machine learning algorithm based on density-based clustering (DBSCAN). Data points are considered to be of the same class if their distance between each other is less than or equal to a specified epsilon. A neighborhood with a minimum number of points within a neighborhood radius is considered a cluster. DBSCAN determines whether two points are similar and belong to the same class. The Dunn index is the minimum distance between any two clusters divided by the maximum distance between the two farthest points within a cluster. The greater the minimum distance between any two clusters (i.e., the distances between cluster samples are far apart), the higher the Dunn index. The smaller the maximum distance between the two farthest points within a cluster (i.e., the distances between cluster samples are close), the higher the Dunn index. If the Dunn index exceeds a preset threshold, the 3D coordinates of the part or model being retrieved are considered similar to those in the material library.

[0063] In an optional manner, the component retrieval submodule and the model retrieval submodule further include:

[0064] Step S1, obtaining various views of the part or model to be retrieved, such as the front view, bottom view, top view, left view, etc.

[0065] Step S2: for any view of the component or model to be retrieved, calculate the 3D coordinate points of the view and the coordinates of each material view in the material library. Figure 3 The first minimum Manhattan distance of the D coordinates is obtained. When the first minimum Manhattan distance is less than a first preset threshold, a first search set is obtained. The Manhattan distance algorithm is suitable for processing 3D coordinate points with discrete attributes and has a fast calculation speed. Alternatively, Euclidean distance, Chebyshev distance, etc. may also be used, but this document is not limited to this.

[0066] Step S3, repeating step S2, respectively calculating the other views of the part or model to be retrieved and the material views in the first retrieval set. Figure 3 The second minimum Manhattan distance of the D coordinate is obtained when the second minimum Manhattan distance is less than a second preset threshold.

[0067] In an alternative approach, such as Figure 5 As shown, the method of performing cluster analysis on the 3D coordinates of the part or model to be retrieved and the 3D coordinates in the material library by using the DBSCAN clustering algorithm to obtain materials similar to the part or model to be retrieved further includes:

[0068] Step S1, using viewpoint entropy and view stability to select the optimal view of the part or model to be retrieved Figure 3 D coordinates. When observing a three-dimensional scene, it is very important to choose a good viewpoint. The viewpoint can be intuitively understood as the observation angle or the camera placement position. Fields such as computational geometry, visual servo, robot motion, and graphics rendering also usually rely on viewpoint selection. Intuitively speaking, the evaluation of a viewpoint should contain more information. In this example, the viewpoint entropy is used to obtain a higher quality viewpoint of the part or model to be retrieved, and the viewpoint entropy and view stability are used to select the optimal viewpoint of the part or model to be retrieved. Figure 3 D coordinate.

[0069] Step S2: Gabor filter is used to filter the optimal view. Figure 3 The D coordinates are convolved (such as CNN network convolution algorithm) to obtain the 3D feature coordinates of the optimal view. Among them, the Gabor filter is a linear filter that can be used for edge detection. Filters in different directions can be used to detect the optimal view. Figure 3The Gabor filter responds to lines connected in different directions of the D coordinate. Similar to human biological vision, in the spatial domain, the 2D Gabor filter is the product of a sinusoidal plane wave and a Gaussian kernel function. This achieves optimal localization in both the spatial and frequency domains. Therefore, it can well describe the scale of the corresponding frequency domain, as well as the spatial distribution and structural information of the line's spatial position and direction selectivity, obtaining the 3D feature coordinates of the optimal view.

[0070] Step S3: using the DBSCAN clustering algorithm to perform cluster analysis on the 3D feature coordinates of the optimal view and the 3D feature coordinates of the optimal view corresponding to each material in the material library, to obtain materials similar to the part or model to be retrieved.

[0071] In an alternative approach, such as Figure 3 As shown, the material retrieval module also includes:

[0072] Step S1, pre-encode the materials in the material library and set a corresponding relationship table between the associated combined materials and material models;

[0073] Step S2, searching the material library for the corresponding combination material and material model according to the material code to be retrieved;

[0074] Step S3: sorting the combined materials and material models according to the information of the number of times the materials are used, the number of times the materials are edited, and the number of times the materials are combined.

[0075] In an optional manner, the material storage module further includes:

[0076] The collected material information, the edited material and the integrated 3D object model are treated as new materials and indexed.

[0077] Specifically, first index information is created for the rendering, lighting, 3D coordinates, and size information of the newly added material;

[0078] Creating second index information for the newly added material and the same material in the material library;

[0079] The third index information is established for the name of the newly added material and the name classification information (such as the trademark name classification method).

[0080] In an alternative approach, such as Figure 4 As shown, the semantic retrieval submodule further includes:

[0081] Step S1: Input the sentence into an LDA topic model to generate a preset number of topics. For example, input the content distribution of multiple words in the sentence into the LDA topic model and specify the number of topics to be generated.

[0082] Step S2: for any LDA topic model, calculate the Euclidean distance of the topic distribution vector between the LDA main model and each material in the material library, and the associated combined material and the material model.

[0083] Step S3: sorting by the Euclidean distance to obtain material statistical information and material combination information corresponding to the sentence.

[0084] In an optional manner, the material design module further includes:

[0085] In response to an edit operation on the 3D object model, the selected material in the 3D object model is retrieved and similar materials and material combination information are displayed. Designers can automatically retrieve similar materials and material combination information based on the selected material during the model editing process, thereby improving design efficiency.

[0086] In response to the replacement operation of the material and the material combination information, the selected material in the 3D object model is replaced. When the designer determines that the material and the material combination information are similar to a material in the 3D object model, the selected material can be replaced and edited.

[0087] The solution provided by the present invention includes: a material collection module, including a design material upload submodule, a design material acquisition submodule, and a design material scanning submodule; a material retrieval module, including a semantic retrieval submodule, a component retrieval submodule, and a model retrieval submodule, for searching a material library and / or collecting materials based on an input sentence, image, or 3D model, to obtain material statistical information and material combination information; wherein the material statistical information includes the number of times a material is used, the number of times a material is edited, and the number of times a material is combined, and the material combination information includes the associated components and associated 3D models of the material; a material design module, for editing and integrating selected materials into a customized 3D object model, generating a public key and a private key based on an asymmetric encryption key generation algorithm, and encrypting the edited materials corresponding to the selected materials and the integrated 3D object model using the private key set by the designer; and a material storage module, for storing the material information collected by the material collection module, and storing the edited materials and the integrated 3D object model in the material design module. The present invention integrates a material management system into the customized 3D object model to perform associated retrieval and storage of materials, thereby improving material management and 3D object design efficiency.

[0088] Figure 8 The schematic diagram of the structure of the computing device embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the computing device.

[0089] like Figure 8As shown, the computing device may include: a processor 802 , a communications interface 804 , a memory 806 , and a communication bus 808 .

[0090] Processor 802, communication interface 804, and memory 806 communicate with each other via communication bus 808. Communication interface 804 is used to communicate with other devices, such as clients or other server network elements. Processor 802 is used to execute program 810, which specifically performs the steps described in the embodiment of the design material management system for customized 3D objects.

[0091] Specifically, the program 810 may include program codes, which include computer operation instructions.

[0092] Processor 802 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in a computing device may be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0093] The memory 806 is used to store the program 810. The memory 806 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0094] The program 810 may be specifically configured to enable the processor 802 to perform the following operations:

[0095] Material collection module, including design material uploading submodule, design material collection submodule and design material scanning submodule;

[0096] A material retrieval module, comprising a semantic retrieval submodule, a component retrieval submodule, and a model retrieval submodule, is configured to retrieve a material library and / or collect materials based on input sentences, images, or 3D models, and obtain material statistics and material combination information; wherein the material statistics include the number of times a material has been used, the number of times a material has been edited, and the number of times a material has been combined; and the material combination information includes the associated components and associated 3D models of the material;

[0097] The material design module is used to edit and integrate the selected materials into the customized 3D object model, generate public and private keys based on an asymmetric encryption key generation algorithm, and encrypt the edited materials corresponding to the selected materials and the integrated 3D object model using the private key set by the designer;

[0098] The material storage module is used to store the material information collected by the material collection module, and to store the edited materials and integrated 3D object models in the material design module.

[0099] In an optional manner, an encryption period is set for the edited material and the integrated 3D object model, and the edited material and the integrated 3D object model are automatically decrypted after the encryption period expires.

[0100] In an optional manner, a DBSCAN clustering algorithm is used to perform cluster analysis on the 3D coordinates of the part or model to be retrieved and the 3D coordinates in the material library to obtain materials similar to the part or model to be retrieved.

[0101] In an optional manner, the component retrieval submodule and the model retrieval submodule further include:

[0102] Step S1, obtaining each view of the component or model to be retrieved;

[0103] Step S2: for any view of the component or model to be retrieved, calculate the 3D coordinate points of the view and the coordinates of each material view in the material library. Figure 3 A first minimum Manhattan distance of the D coordinate, when the first minimum Manhattan distance is less than a first preset threshold, a first search set is obtained;

[0104] Step S3, repeating step S2, respectively calculating the other views of the part or model to be retrieved and the material views in the first retrieval set. Figure 3 The second minimum Manhattan distance of the D coordinate is obtained when the second minimum Manhattan distance is less than a second preset threshold.

[0105] In an optional manner, performing cluster analysis on the 3D coordinates of the part or model to be retrieved and the 3D coordinates in the material library using the DBSCAN clustering algorithm to obtain materials similar to the part or model to be retrieved further includes:

[0106] Step S1, using viewpoint entropy and view stability to select the optimal view of the part or model to be retrieved Figure 3 D coordinate;

[0107] Step S2: Gabor filter is used to filter the optimal view. Figure 3 The D coordinates are convolved to obtain the 3D feature coordinates of the optimal view;

[0108] Step S3: using the DBSCAN clustering algorithm to perform cluster analysis on the 3D feature coordinates of the optimal view and the 3D feature coordinates of the optimal view corresponding to each material in the material library, to obtain materials similar to the part or model to be retrieved.

[0109] In an optional manner, the material retrieval module further includes:

[0110] Step S1, pre-encode the materials in the material library and set a corresponding relationship table between the associated combined materials and material models;

[0111] Step S2, searching the material library for the corresponding combination material and material model according to the material code to be retrieved;

[0112] Step S3: sorting the combined materials and material models according to the information of the number of times the materials are used, the number of times the materials are edited, and the number of times the materials are combined.

[0113] In an optional manner, the material storage module further includes:

[0114] The collected material information, the edited material, and the integrated 3D object model are treated as new materials and indexed;

[0115] Specifically, first index information is created for the rendering, lighting, 3D coordinates, and size information of the newly added material;

[0116] Creating second index information for the newly added material and the same material in the material library;

[0117] A third index information is established for the name and name classification information of the newly added material.

[0118] In an optional manner, the semantic retrieval submodule further includes:

[0119] Step S1, inputting the sentence into the LDA topic model to generate a preset number of topics;

[0120] Step S2: for any LDA topic model, calculate the Euclidean distance of the topic distribution vector between the LDA subject model and each material in the material library, as well as the associated combined material and the material model;

[0121] Step S3: sorting by the Euclidean distance to obtain material statistical information and material combination information corresponding to the sentence.

[0122] In an optional manner, the material design module further includes:

[0123] In response to an editing operation on the 3D object model, obtaining a material selected in the 3D object model and displaying materials and material combination information similar to the material;

[0124] In response to a replacement operation on the material and the material combination information, the selected material in the 3D object model is replaced.

[0125] The algorithm or demonstration provided herein are not inherently relevant to any particular computer, virtual system or other equipment. Various general-purpose systems can also be used together with the teachings based on this. According to the above description, it is apparent that the structure required for constructing this type of system. In addition, the embodiment of the present invention is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the above description of specific languages ​​is for the purpose of disclosing the best mode of the present invention.

[0126] In the description provided herein, numerous specific details are described. However, it is understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of this description.

[0127] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Accordingly, the claims that follow the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of the present invention.

[0128] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition may be divided into multiple submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed herein may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0129] Furthermore, those skilled in the art will appreciate that although some embodiments herein include certain features included in other embodiments but not other features, combinations of features from different embodiments are intended to be within the scope of the present invention and to form different embodiments. For example, in the claims below, any of the claimed embodiments may be used in any combination.

[0130] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components according to an embodiment of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for executing a part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0131] It should be noted that the above embodiments illustrate rather than limit the invention, and that alternative embodiments may be devised by a person skilled in the art without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments should not be understood as limiting the order of execution unless otherwise specified.

Claims

1. A design material management system based on 3D object customization, characterized by: include: Material collection module, including design material uploading submodule, design material collection submodule and design material scanning submodule; A material retrieval module, comprising a semantic retrieval submodule, a component retrieval submodule, and a model retrieval submodule, is configured to retrieve a material library and / or collect materials based on input sentences, images, or 3D models, and obtain material statistics and material combination information; wherein the material statistics include the number of times a material has been used, the number of times a material has been edited, and the number of times a material has been combined; and the material combination information includes the associated components and associated 3D models of the material; The material design module is used to edit and integrate the selected materials into the customized 3D object model, generate public and private keys based on an asymmetric encryption key generation algorithm, and encrypt the edited materials corresponding to the selected materials and the integrated 3D object model using the private key set by the designer; a material storage module, configured to store the material information collected by the material collection module, and to store the edited materials and integrated 3D object models in the material design module; The component retrieval submodule and the model retrieval submodule further include: Use the DBSCAN clustering algorithm to perform cluster analysis on the 3D coordinates of the part or model to be retrieved and the 3D coordinates in the material library to obtain materials similar to the part or model to be retrieved; The method of performing cluster analysis on the 3D coordinates of the part or model to be retrieved and the 3D coordinates in the material library by using the DBSCAN clustering algorithm to obtain materials similar to the part or model to be retrieved further includes: Step S1, selecting the optimal view 3D coordinates of the component or model to be retrieved by using viewpoint entropy and view stability; Step S2, performing convolution processing on the optimal view 3D coordinates using a Gabor filter to obtain the 3D feature coordinates of the optimal view; Step S3: using the DBSCAN clustering algorithm to perform cluster analysis on the 3D feature coordinates of the optimal view and the 3D feature coordinates of the optimal view corresponding to each material in the material library, to obtain materials similar to the part or model to be retrieved.

2. The design material management system based on 3D object customization according to claim 1, characterized in that: After or while encrypting the edited material and the integrated 3D object model corresponding to the selected material using the private key set by the designer, the material design module further includes: An encryption period is set for the edited material and the integrated 3D object model, and the edited material and the integrated 3D object model are automatically decrypted after the encryption period is reached.

3. The design material management system based on 3D object customization according to claim 1, characterized in that: The component retrieval submodule and the model retrieval submodule also include: Step S1, obtaining each view of the component or model to be retrieved; Step S2, for any view of the component or model to be retrieved, calculating a first minimum Manhattan distance between the 3D coordinate point of the view and the 3D coordinates of each material view in the material library, and obtaining a first search set when the first minimum Manhattan distance is less than a first preset threshold; Step S3, repeating step S2, respectively calculating the second minimum Manhattan distance between other views of the component or model to be retrieved and the 3D coordinates of each material view in the first retrieval set. When the second minimum Manhattan distance is less than a second preset threshold, a second retrieval set is obtained.

4. The design material management system based on 3D object customization according to claim 1, characterized in that: The material retrieval module also includes: Step S1, pre-encode the materials in the material library and set a corresponding relationship table between the associated combined materials and material models; Step S2, searching the material library for the corresponding combination material and material model according to the material code to be retrieved; Step S3: sorting the combined materials and material models according to the information of the number of times the materials are used, the number of times the materials are edited, and the number of times the materials are combined.

5. The design material management system based on 3D object customization according to claim 1, characterized in that: The material storage module further includes: The collected material information, the edited material, and the integrated 3D object model are treated as new materials and indexed; Specifically, first index information is created for the rendering, lighting, 3D coordinates, and size information of the newly added material; Creating second index information for the newly added material and the same material in the material library; A third index information is established for the name and name classification information of the newly added material.

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