Holographic three-dimensional image processing method, device, equipment and storage medium

Abstract

The present disclosure provides a holographic three-dimensional image processing method, device, equipment and storage medium, the method comprises: performing a component selection operation on a base model to obtain at least one first component combination, the base model is composed of m components connected, n components are included in the first component combination, 1 The method of the present disclosure is quick and flexible in adjusting the interface arrangement according to the changes of three-dimensional image data.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of computers, and in particular, to a holographic three-dimensional image processing method, device, equipment and storage medium. BACKGROUND

[0002] In holographic three-dimensional image applications, the coordination of three-dimensional interface arrangement and aesthetics is one of the important factors. When the data of the holographic three-dimensional image changes, it is generally necessary to manually re-arrange the three-dimensional interface arrangement of the three-dimensional model according to the changed data, and construct a new three-dimensional model. This method cannot quickly and flexibly make changes to the interface arrangement according to the data changes, and lacks flexibility. SUMMARY

[0003] The present disclosure provides a holographic three-dimensional image processing method, device, equipment and storage medium to at least solve the above technical problems existing in the prior art.

[0004] According to a first aspect of the present disclosure, a holographic three-dimensional image processing method is provided, the method comprising:

[0005] Performing a component selection operation on a base model to obtain at least one first component combination, the base model being composed of m components connected, and the first component combination including n components, 1 < n < m;

[0006] Filtering the first component combination according to the relationship between the components in the first component combination;

[0007] Obtaining a target model based on the filtering result.

[0008] In an implementable manner, one of the m components is a main component, and the rest are auxiliary components, the auxiliary components are directly or indirectly connected with the main component, and the first component combination includes the main component.

[0009] In an implementable manner, filtering the first component combination comprises:

[0010] Deleting at least one isolated component combination in the first component combination to obtain at least one second component combination, the isolated component combination being the first component combination in which the n components cannot be connected as a whole.

[0011] In an implementable manner, the isolated component combination includes an isolated component, and the isolated component is an auxiliary component that has no direct or indirect connection relationship with the main component in the isolated component combination.

[0012] In an implementable manner, obtaining a target model based on the filtering result comprises:

[0013] According to a discrete degree of the components in at least one second component combination, the second component combination with the highest discrete degree is selected as the component combination of the target model, and the at least one second component combination is obtained by screening the first component combination.

[0014] In an implementation, according to a discrete degree of the components in at least one second component combination, the second component combination with the highest discrete degree is selected as the component combination of the target model, and the at least one second component combination is obtained by screening the first component combination, including:

[0015] Obtaining a mean square deviation of the spatial coordinates of the positions of the components in the second component combination;

[0016] According to the mean square deviation, the discrete degree of the components in the second component combination is determined, and the discrete degree is proportional to the mean square deviation.

[0017] In an implementation, the mean square deviation of the spatial coordinates of the positions of the components is obtained, including:

[0018] Obtaining a centroid coordinate of each component in the second component combination;

[0019] Calculating a mean square deviation of the spatial coordinates of the components in three directions respectively according to the centroid coordinate of the components;

[0020] Summing the mean square deviations of the spatial coordinates of all the components in the second component combination in three directions as a discrete coefficient of the components in the second component combination, and the discrete degree is proportional to the discrete coefficient.

[0021] According to a second aspect of the present disclosure, a holographic three-dimensional image processing device is provided, and the device includes:

[0022] A pre-selection module is configured to perform a component selection operation on a base model to obtain at least one first component combination, the base model is composed of m components connected together, and the first component combination includes n components, 1 < n < m;

[0023] A screening module is configured to screen the first component combination according to relationships between the components in the first component combination;

[0024] A determination module is configured to obtain a target model based on a screening result.

[0025] According to a third aspect of the present disclosure, an electronic device is provided, and the electronic device includes:

[0026] At least one processor; and

[0027] A memory connected in communication with the at least one processor; wherein

[0028] The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method of the present disclosure.

[0029] According to a fourth aspect of the present disclosure, a non-transitory computer readable storage medium storing computer instructions is provided, the computer instructions being used to cause the computer to perform the method of the present disclosure.

[0030] In the holographic three-dimensional image processing method, device, equipment and storage medium of the present disclosure, at least one first component combination can be obtained by performing component selection operation on the basic model, the basic model is composed of m components connected, n components are included in the first component combination, 1 < n < m, when the data changes, all possible combinations of the n components can be obtained, the first component combination is filtered according to the existing relationship between each component in the first component combination, and based on the filtering result, the target model can be obtained from all possible combinations, and the target model after the interface arrangement changes can be quickly and flexibly obtained according to the change of the data.

[0031] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0032] The above and other objects, features and advantages of the exemplary embodiments of the present disclosure will be more apparent from the following detailed description read in conjunction with the accompanying drawings, in which:

[0033] In the drawings, identical or corresponding reference numerals indicate identical or corresponding parts.

[0034] Figure 1 A three-dimensional model schematic diagram to which the holographic three-dimensional image processing method of the embodiment of the present disclosure is specifically applied is shown Figure 1 ;

[0035] Figure 2 A three-dimensional model schematic diagram to which the holographic three-dimensional image processing method of the embodiment of the present disclosure is specifically applied is shown Figure 2 ;

[0036] Figure 3 A flowchart of the implementation of the holographic three-dimensional image processing method of the embodiment of the present disclosure is shown

[0037] Figure 4 A structure schematic diagram of the holographic three-dimensional image processing device of the embodiment of the present disclosure is shown

[0038] Figure 5 A schematic diagram of a constituent structure of an electronic device is shown. DETAILED DESCRIPTION

[0039] To make the objectives, characteristics and advantages of the present disclosure more obvious and easy to understand, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present disclosure.

[0040] Holographic three-dimensional images are widely used in various museums, theme parks, city planning exhibition halls, science and technology museums, entertainment halls, exhibitions, fairs, etc. For example, knowledge points can be combined with holographic three-dimensional images to realize teaching and popularization through holographic three-dimensional images. According to specific conditions, the data of the holographic three-dimensional image, such as the number of components, may change, which requires adjusting the arrangement of the three-dimensional interface to obtain a target model to meet the demand for beauty and coordination. For example Figure 1 The forest shown can be combined with a knowledge system structure to visualize the knowledge system through holographic three-dimensional images in the form of forests, woods, trees, branches, etc. In different cases, the knowledge points to be displayed may change, for example Figure 2 The knowledge points in the tree shown change, and accordingly the number of components of the holographic three-dimensional image, such as the number of branches, also changes. According to the actual demand for the number of components, the spatial relationship of the components is arranged to meet the demand for beauty, coordination, etc. to obtain a target model. The holographic three-dimensional image processing method of the present disclosure can quickly and flexibly realize the corresponding interface arrangement change according to the change of the data of the holographic three-dimensional image. The holographic three-dimensional image model of the knowledge forest will be taken as an example to illustrate the embodiments of the present disclosure.

[0041] Referring to Figure 3 A holographic three-dimensional image processing method, the method comprising:

[0042] Performing a component selection operation on a basic model to obtain at least one first component combination, the basic model being composed of m components connected together, and the first component combination including n components, 1 < n < m; n is the actual number of components of the target model, and the actual number of components is determined according to actual demand. Taking the model of the knowledge forest as an example, when the knowledge points to be displayed change, the number of components corresponding to the knowledge points, such as the number of branches, also changes, according to which the actual number of components of the final required model, i.e. the target model, can be determined.

[0043] According to the relationship between the components in the first component combination, the first component combination is filtered;

[0044] Based on the screening result, a target model is obtained.

[0045] In the holographic three-dimensional image processing method of the present disclosure, by performing a component selection operation on a basic model, at least one first component combination is obtained, the basic model is composed of m components, n components are included in the first component combination, 1 < n < m, when data changes, all possible combinations of n components are obtained, the first component combination is screened according to the existing relationship between the components in the first component combination, and based on the screening result, a target model can be obtained from all possible combinations. According to the required actual number of components n, the model after the interface arrangement adaptively changes, that is, the target model, is quickly and flexibly obtained.

[0046] In the embodiment of the present disclosure, the basic model includes m components, and m is the maximum number of components of the target model. Referring to Figure 2 , when constructing a three-dimensional model of a tree level, one branch can represent one knowledge point, for example, a tree can represent a phylum, class, genus, etc. of animals, and branches, leaves, etc. can further classify and refine knowledge points. Of course, the knowledge displayed by the knowledge forest is not limited to this, for example, it can also be astronomical knowledge, weapon knowledge, mathematical knowledge, etc. The maximum number of components (branches) m of the basic model is determined according to all the knowledge points contained in the tree. According to the structure of m branches, the basic model of the tree is constructed in an artistic manner, so that the parameters of each branch, including style, position and connection relationship, are determined.

[0047] Referring to Figure 2 , when constructing the basic model, the initial connection relationship of the branch can be manually determined by the designer, so that the specific connection relationship of each branch in space can be determined. In the example embodiment, referring to Figure 1 and Figure 2 , each component can have a separate number as the identity of the component. For example, Figure 1 each tree is numbered with a number, Figure 2 the branches in Figure 2 can be numbered with letters as the identity of the branch. Each component can have a connection relationship list, and the connection relationship list of each component includes the component number having a connection relationship with it. Figure 2 In the example shown in the figure, the trunk can be regarded as a special branch. The branch can be directly connected to the trunk, or indirectly connected to the trunk through other branches. The connection relationship between the branches includes direct connection and indirect connection. For example, branch a and branch b are both connected to trunk t, so branch a and branch b are considered to have a connection relationship, that is, branch a and branch b form a connected path through trunk t.

[0048] In an implementation, one of the m components is a main component, and the rest are sub-components, the sub-components are directly or indirectly connected with the main component, and the first component combination includes the main component. See Figure 2 In a three-dimensional model of a tree level, the main component may be, for example, a tree trunk, and the sub-components may be, for example, branches. See Figure 1 In a three-dimensional model of a forest level, the main component may be, for example, a mountain peak or the earth, and the sub-components may be, for example, trees, vines, and the like.

[0049] In the embodiments of the present disclosure, the first component combination is screened according to the relationship between the components in the first component combination. Since all the components in the first component combination are selected from the components of the basic model, and the relationship between all the components is determined based on the parameters of the components of the basic model, the first component combination can be quickly screened according to the relationship between the components in the first component combination.

[0050] In an implementation, the first component combination is screened, including: deleting at least one isolated component combination in the first component combination to obtain at least one second component combination, the isolated component combination being a first component combination in which the n components cannot be connected together. For example, in the isolated component combination, the n components are divided into at least two parts, the components in each part can be connected together, and there is no connection relationship between the parts, so such a component combination cannot be connected together and the visual effect is poor. In the embodiments of the present disclosure, the first component combination is screened to obtain at least one second component combination, and in the second component combination, the n components are directly or indirectly connected. The first component combination in which the n components cannot be connected together is not included in the screening result, so as to avoid the lack of integrity of the model and affect the aesthetics.

[0051] In an implementation, the isolated component combination includes an isolated component, and the isolated component is a sub-component that has no direct or indirect connection relationship with the main component in the isolated component combination. In the embodiments of the present disclosure, whether the first component combination is an isolated component combination can be determined according to whether the first component combination includes an isolated component. If the first component combination includes an isolated component, the first component combination is an isolated component combination and needs to be deleted. See Figure 2 For example, in the basic model, branch a is directly connected with tree trunk t, and branch b is directly connected with branch a, but branch b is not directly connected with tree trunk t and other branches. If the first component combination does not include branch a, then branch b has no direct or indirect connection relationship with tree trunk t and becomes an isolated component because b is not directly connected with tree trunk t and is not connected with other branches except a. Alternatively, branch c is directly connected with branch b described above and has no direct connection relationship with other branches. When the first component combination does not include branch a, then although branch b and branch c are connected, the combination of branch b and branch c has no direct or indirect connection relationship with tree trunk t and becomes an isolated component.

[0052] In the embodiments of the present disclosure, the screening of the first component combination can obtain at least one second component combination, for example, after deleting the isolated component combination in the first component combination, the remaining component combination is the second component combination.

[0053] In an implementation, based on the screening result, the target model is obtained, including: according to the dispersion degree of the components in the at least one second component combination, taking the second component combination with the highest dispersion degree as the component combination constituting the target model, and the at least one second component combination is obtained by screening the first component combination. In the embodiments of the present disclosure, the target model is obtained according to the dispersion degree of the components, and the higher the dispersion degree of the components, the better the spatial rendering effect of the final model, for example, the tree, and the beauty of the construction effect is guaranteed.

[0054] In an implementation, according to the dispersion degree of the components in the at least one second component combination, taking the second component combination with the highest dispersion degree as the component combination constituting the target model, including: obtaining the mean square deviation of the spatial coordinates of the positions of the components in the second component combination; and determining the dispersion degree of the components in the second component combination according to the mean square deviation, and the dispersion degree is proportional to the mean square deviation. In the embodiments of the present disclosure, each component in the second component combination is selected from the components of the basic model, and according to the parameters of each component of the basic model, the spatial relationship of each component can be determined, including the position and connection relationship of the component in space, etc. For example, the position of the component in space can be determined by the spatial coordinates, and the mean square deviation can better describe the deviation degree of the spatial coordinate values of each component from the mean value, and can better represent the dispersion degree.

[0055] In an implementation, obtaining the mean square deviation of the spatial coordinates of the positions of the components includes: obtaining the centroid coordinates of each component in the second component combination; calculating the mean square deviation of the components in three direction coordinates respectively with the centroid coordinates as the spatial coordinates of the components; and summing the mean square deviations of the three direction coordinates of all the components in the second component combination as the dispersion coefficient of the components in the second component combination, and the dispersion degree is proportional to the dispersion coefficient. In the embodiments of the present disclosure, the centroid coordinates of each component are taken as the spatial coordinates of the components, and the centroid position represents the position of the component in space, which can more accurately express the actual distribution of the component in space. For example, when constructing the model of a tree, the mean square deviation σx of the branches in the coordinate x, the mean square deviation σy of the branches in the coordinate y, and the mean square deviation σz of the branches in the coordinate z are obtained respectively, and then the sum (σx+σy+σz) of the mean square deviations of all the branches in the combination in each coordinate is taken as the dispersion coefficient of the branch combination. The larger the dispersion coefficient is, the larger the branches deviate from the overall center, and then it is considered that the dispersion degree is higher. On the contrary, if the dispersion coefficient is smaller, it means that the branches are near the overall center, and then it is considered that the dispersion degree is lower.

[0056] In the embodiments of the present disclosure, the second component combination with the highest degree of dispersion is combined as the component combination constituting the target model, and the target model of the corresponding tree can be constituted through the relationship of each component in the second component combination.

[0057] The above embodiments are described by taking the tree level model construction as an example, and the branches are the components of the model. The construction principle of the forest level model is the same as that of the tree model, and the tree and the like can be taken as the components of the forest level model. The maximum number m of components contained in the base model of the forest level is determined, and the panoramic base model is designed according to the maximum number m. In the specific construction, the first component combination is selected according to the actual number of components, the first component combination is screened, the best component combination is selected from the screening results according to the spatial dispersion distribution and the like, and the final target model is obtained.

[0058] In the holographic three-dimensional image processing method of the embodiments of the present disclosure, the base model with the maximum number of components can be constructed according to the visualization features, and the overall effect is presented. Then, each component of the base model is taken as a different subset, the first component combination of n components is selected from the m components based on the base model without repetition according to the component number n required by the target model, and the target model with beautiful component effect can be obtained based on at least one first component combination obtained by the above selection through screening. Flexibility of automatic construction is realized, and the beauty of the construction effect is ensured.

[0059] Referring to Figure 4 The present disclosure provides a holographic three-dimensional image processing device, which comprises a pre-selection module, a screening module and a determination module. The pre-selection module is used to perform a component selection operation on a base model to obtain at least one first component combination. The base model is composed of m components connected together, and the first component combination comprises n components, 1

[0060] In the holographic three-dimensional image processing device of the present disclosure, the pre-selection module can obtain at least one first component combination by performing a component selection operation on the base model. The base model is composed of m components connected together, and the first component combination comprises n components, 1

[0061] In an implementable manner, one of the m components is a main component, and the rest are auxiliary components. The auxiliary components are directly or indirectly connected with the main component, and the first component combination comprises the main component.

[0062] In an implementation, the screening module screens the first component combination, including: deleting an isolated component combination in at least one first component combination to obtain at least one second component combination, the isolated component combination being a first component combination in which n components cannot be connected as a whole.

[0063] In an implementation, the isolated component combination includes an isolated component, the isolated component being a secondary component in the isolated component combination that has no direct or indirect connection relationship with a primary component.

[0064] In an implementation, the determining module obtains the target model based on the screening result, including: according to a dispersion degree of components in the at least one second component combination, taking the second component combination with the highest dispersion degree as the component combination constituting the target model, the at least one second component combination being obtained by screening the first component combination. In the embodiment of the present disclosure, the target model is obtained according to the dispersion degree of the components, and the higher the dispersion degree of the components, the better the spatial rendering effect of the final model, such as a tree, and the aesthetic appearance of the construction effect is guaranteed.

[0065] In an implementation, the determining module obtains the target model based on the screening result, including: according to a dispersion degree of components in the at least one second component combination, taking the second component combination with the highest dispersion degree as the component combination constituting the target model, the at least one second component combination being obtained by screening the first component combination. In the embodiment of the present disclosure, the target model is obtained according to the dispersion degree of the components, and the higher the dispersion degree of the components, the better the spatial rendering effect of the final model, such as a tree, and the aesthetic appearance of the construction effect is guaranteed.

[0066] In an implementation, the determining module obtains the target model based on the screening result, including: according to a dispersion degree of components in the at least one second component combination, taking the second component combination with the highest dispersion degree as the component combination constituting the target model, the at least one second component combination being obtained by screening the first component combination. In the embodiment of the present disclosure, the target model is obtained according to the dispersion degree of the components, and the higher the dispersion degree of the components, the better the spatial rendering effect of the final model, such as a tree, and the aesthetic appearance of the construction effect is guaranteed.

[0067] The holographic three-dimensional image processing device of the embodiment of the present disclosure can implement the method of the above-mentioned embodiment. The description of the holographic three-dimensional image processing device embodiment above is similar to the description of the above-mentioned method embodiment, and has similar beneficial effects as the above-mentioned method embodiment, and thus is not described in detail. For the technical details of the holographic three-dimensional image processing device embodiment of the present disclosure that have not been disclosed, please refer to the description of the above-mentioned method embodiment for understanding. In order to save space, the description is not repeated.

[0068] According to the embodiments of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.

[0069] Figure 5A schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present disclosure described and / or claimed in this document.

[0070] As shown in Figure 5 The device 500 includes a computing unit 501 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 502 or a computer program loaded into a random access memory (RAM) 503 from a storage unit 508. Various programs and data required for the operation of the device 500 can also be stored in the RAM 503. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0071] Various components in the device 500 are connected to the I / O interface 805, including an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a magnetic disk, a magneto-optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0072] The computing unit 501 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 501 performs various methods and processes described above, such as the holographic three-dimensional image processing method. For example, in some embodiments, the holographic three-dimensional image processing method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded onto the RAM 503 and executed by the computing unit 501, one or more steps of the holographic three-dimensional image processing method described above can be performed. Alternatively, in other embodiments, the computing unit 501 can be configured to perform the holographic three-dimensional image processing method by any other appropriate means, such as by means of firmware.

[0073] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0074] Program code for carrying out methods of the present disclosure can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces a means for implementing the functions / acts specified in the flowcharts and / or block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0075] In the context of this disclosure, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0076] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0077] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0078] The computer system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0079] It should be understood that the various forms of flow shown above can be used to reorder, add, or delete steps. For example, the steps described in the present disclosure can be performed in parallel, in series, or in a different order, as long as the desired results of the technical solutions of the present disclosure can be achieved, which are not limited herein.

[0080] In addition, the terms "first", "second", are only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0081] The above is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present disclosure, which should be covered within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

Claims

1. A holographic three-dimensional image processing method, the method is applied to the interface arrangement adjustment when the data dynamically changes in the holographic three-dimensional image, characterized in that, The method comprises: performing a component selection operation on a base model to obtain at least one first component combination, the base model being composed of m component connections, the first component combination including n components, 1 one of the m components is a main component, and the rest are auxiliary components, the auxiliary components being directly or indirectly connected to the main component, and the first component combination including the main component; screening the first component combination according to spatial relationships between components in the first component combination; the screening of the first component combination comprises: deleting at least one isolated component combination in the first component combination to obtain at least one second component combination, the isolated component combination being the first component combination in which there is an auxiliary component having no direct or indirect connection relationship with the main component and being unable to be connected as a whole; obtaining a target model based on the screening result, the target model being used for visual presentation of the holographic three-dimensional image.

2. The method of claim 1, wherein, The isolated component combination includes an isolated component, which is an auxiliary component having no direct or indirect connection relationship with the main component in the isolated component combination.

3. The method of claim 1, wherein, The obtaining of the target model based on the screening result comprises: according to a dispersion degree of components in at least one second component combination, taking the second component combination with the highest dispersion degree as a component combination constituting the target model, the at least one second component combination being obtained by screening the first component combination.

4. The method of claim 3, wherein, According to a dispersion degree of components in at least one second component combination, taking the second component combination with the highest dispersion degree as a component combination constituting the target model, comprises: obtaining a mean square deviation of spatial coordinates of positions of the components in the second component combination; determining the dispersion degree of the components in the second component combination according to the mean square deviation, the dispersion degree being directly proportional to the mean square deviation.

5. The method of claim 4, wherein, The obtaining of the mean square deviation of spatial coordinates of positions of the components comprises: obtaining centroid coordinates of the components in the second component combination; respectively calculating mean square deviations of three-direction coordinates of the components in the second component combination according to the centroid coordinates as the spatial coordinates of the components; summing the mean square deviations of the three-direction coordinates of all the components in the second component combination as a dispersion coefficient of the components in the second component combination, the dispersion degree being directly proportional to the dispersion coefficient.

6. A holographic three-dimensional image processing device, which is applied to interface arrangement adjustment when data in a holographic three-dimensional image dynamically changes, characterized in that, The device comprises: a pre-selection module configured to perform a component selection operation on a base model to obtain at least one first component combination, the base model being composed of m component connections, the first component combination including n components, 1 a screening module configured to screen the first component combination according to spatial relationships between components in the first component combination; the screening module is further configured to delete at least one isolated component combination in the first component combination to obtain at least one second component combination, the isolated component combination being the first component combination in which there is an auxiliary component having no direct or indirect connection relationship with the main component and being unable to be connected as a whole; determining module configured to obtain, based on the screening result, a target model for visual presentation of the holographic three-dimensional image.

7. An electronic device, comprising: comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

8. A non-transitory computer-readable storage medium having stored thereon computer instructions, wherein, the computer instructions are configured to cause the computer to perform the method of any one of claims 1-5.

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