WO2021254383A1 - 人体模型数据处理方法、装置、电子设备及存储介质 - Google Patents

人体模型数据处理方法、装置、电子设备及存储介质 Download PDF

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Publication number
WO2021254383A1
WO2021254383A1 PCT/CN2021/100335 CN2021100335W WO2021254383A1 WO 2021254383 A1 WO2021254383 A1 WO 2021254383A1 CN 2021100335 W CN2021100335 W CN 2021100335W WO 2021254383 A1 WO2021254383 A1 WO 2021254383A1
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data
human body
body model
subcontracting
sub
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PCT/CN2021/100335
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English (en)
French (fr)
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李继楠
白桦
王秉东
刘阳阳
白光
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京东方科技集团股份有限公司
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Priority to US17/790,748 priority Critical patent/US20230041874A1/en
Publication of WO2021254383A1 publication Critical patent/WO2021254383A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T19/00Manipulating 3D models or images for computer graphics
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T19/00Manipulating 3D models or images for computer graphics
    • G06T19/20Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/21Design, administration or maintenance of databases
    • G06F16/215Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/23Updating
    • G06F16/2379Updates performed during online database operations; commit processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/248Presentation of query results
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/55Clustering; Classification
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/003D [Three Dimensional] image rendering
    • G06T15/04Texture mapping
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/60Type of objects
    • G06V20/64Three-dimensional objects
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2210/00Indexing scheme for image generation or computer graphics
    • G06T2210/41Medical
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00Indexing scheme relating to image or video recognition or understanding
    • G06V2201/03Recognition of patterns in medical or anatomical images

Definitions

  • the present disclosure relates to the field of Internet data processing technology. Specifically, the present disclosure relates to a human body model data processing method, device, electronic equipment, and storage medium.
  • the human body 3D model not only occupies a large data space, but also carries a huge number of texture files that occupy a huge data space at the same time.
  • the present disclosure provides a human body model data processing method, including:
  • the predetermined classification conditions include medical anatomy classification information and art resource category information;
  • each grouped data determine the repeated resources in the grouped data and the sorted grouped data after removing the repeated resources
  • the repeated resources are packaged into sub-packaged data, and the sorted grouped data are respectively packaged into sub-packaged data, and all the packaged data is stored.
  • the classification of the three-dimensional human body model into a plurality of grouped data according to a predetermined classification condition includes:
  • the medical anatomy classification information determine the medical anatomy classification data group of the three-dimensional human body data
  • the art resource category information corresponding to the medical anatomy system classification is determined, and the art resource data corresponding to the art resource category information in the three-dimensional human body model data is allocated to the medical anatomy classification data group to obtain several grouped data.
  • the method further includes:
  • the determining repeated resources in the grouped data according to each grouped data, and the sorted grouped data after the repeated resources are removed include:
  • the public information in the human medical anatomy classification information extract the data related to the public information from the several grouped data and perform deduplication processing to obtain the duplicate resource;
  • the data related to the public information is deleted from the plurality of grouped data to obtain the sorted grouped data.
  • the art resource data includes a skeleton model frame and a texture attached to the rich skeleton model frame.
  • the packaging of the repeated resources into sub-packaged data, and the packing of the sorted grouped data into sub-packaged data respectively includes:
  • the storing all the packet data includes:
  • the medical anatomy classification information includes at least one of the following: human body shape classification information, human organ classification information, or human body system classification information; art resource category information includes two-dimensional resource information and three-dimensional resource information .
  • the packaging of the repeated resources into sub-packaged data, and the separately packaged grouped data after sorting into sub-packaged data, and storing all of the packaged data includes:
  • the packaging of repeated resources into sub-packaged data, and each sorted grouped data are respectively packaged into sub-packaged data, and after storing all of the packaged data, the method further includes:
  • the subcontracting catalog table is determined according to the sorted human body system grouping data.
  • the subcontracting catalog table includes multiple pieces of mapping information corresponding to the subcontracting data of the human body system.
  • the subcontracting data of the human body system includes: sports system subcontracting data, nervous system Subcontracting data, endocrine system subcontracting data, circulatory system subcontracting data, respiratory system subcontracting data, digestive system subcontracting data, urinary system subcontracting data, and reproductive system subcontracting data;
  • the subpackage data corresponding to the viewing request is obtained and displayed.
  • the present disclosure provides a method for displaying human body model data, including:
  • the human body model subcontracting data is determined by the human body model data optimization method provided in the first aspect of the present disclosure
  • obtaining subpackage data of the human body model corresponding to the data query instruction includes:
  • the subcontracted data of the human body system includes: subcontracted data of the motor system, subcontracted data of the nervous system, subcontracted data of the endocrine system, subcontracted data of the circulatory system, subcontracted data of the respiratory system, subcontracted data of the digestive system, subcontracted data of the urinary system, and reproduction System subcontracting data;
  • the human body system subcontracting data corresponding to the viewing request is obtained.
  • a human body model data processing device including:
  • the grouping module is used to obtain three-dimensional human body model data, and classify the three-dimensional human body model data into several grouped data according to predetermined classification conditions.
  • the predetermined classification conditions include medical anatomy classification information and art resource category information;
  • the sorting module is used to determine the repeated resources in the grouped data according to each grouped data, and the sorted grouped data after removing the repeated resources;
  • the packing module is used to pack repeated resources into sub-packed data, pack each sorted grouped data into sub-packed data respectively, and store all part of the packed data.
  • the present disclosure provides an electronic device, including a display, and further including:
  • the memory is electrically connected to the processor
  • At least one program is stored in the memory and configured to be executed by the processor, and at least one program is configured to: implement the human body model data processing method described in the first aspect of the present disclosure or the human body model described in the second aspect Data presentation method.
  • the present disclosure provides a computer-readable storage medium, and the computer-readable storage medium stores at least one instruction, at least one program, code set or instruction set, at least one instruction, at least one program, code set or instruction The set is loaded and executed by the processor to implement the human body model data processing method described in the first aspect of the present disclosure or the human body model data display method described in the second aspect.
  • FIG. 1 is a schematic flowchart of a method for processing human body model data according to an embodiment of the disclosure
  • FIG. 2 is a schematic diagram of the process of classifying a three-dimensional human body model into a number of grouped data according to a predetermined classification condition according to an embodiment of the disclosure
  • FIG. 3 is a schematic diagram of a process of determining repeated resources in the grouped data according to each grouped data, and sorted grouped data after removing the repeated resources according to an embodiment of the present disclosure
  • FIG. 4 is a schematic flow chart of a method for processing human body model data provided by an example of the present disclosure
  • FIG. 5 is a flowchart of a data query example of a human body model in the disclosure.
  • FIG. 6 is a schematic diagram of the structure of a human body model data processing device provided by an embodiment of the disclosure.
  • FIG. 7 is a schematic frame diagram of the structure of an electronic device for processing human body model data according to an embodiment of the disclosure.
  • the human body model data processing method, device, electronic equipment, and storage medium provided in the present disclosure are intended to solve the above technical problems of related technologies.
  • the embodiment of the first aspect of the present disclosure provides a human body model data processing method, as shown in FIG. 1, including the following steps:
  • S100 Acquire three-dimensional human body model data, and classify the three-dimensional human body model data into a number of grouped data according to predetermined classification conditions.
  • the predetermined classification conditions include medical anatomy classification information and art resource category information.
  • S300 Pack the repetitive resources into sub-package data, respectively package the sorted grouped data into sub-package data, and store all the package data.
  • the device obtains three-dimensional human body model data.
  • the three-dimensional human body model data is raw data input from the outside.
  • the device here may be a terminal device or a server.
  • the classified data is de-duplicated, and the redundant and repeated resources in the grouped data are sorted to avoid the phenomenon of resource redundancy.
  • the grouping of data is clearer and facilitates data management.
  • S200 obtains the clearly grouped grouped data, the grouped data is packaged into sub-packaged data through the data packaging operation through S300.
  • the complete 3D human body model data is composed of several sub-packaged data, and these sub-packaged data are interconnected and mutually connected. Independent, users can choose one or several to load and run.
  • the human body model data processing method provided by the present disclosure subdivides the complete three-dimensional human body model data into several groups according to the characteristics of medical anatomy classification information and art resource classification information, and sorts and removes the duplication of the grouped data, and packs them into independent groups.
  • the subcontracting data of the complete 3D human body model data is divided into zeros, so that the user can load the data required by the user according to the needs, instead of loading all the 3D human body data at one time, so as to solve the problem of the software when downloading or loading the 3D human body model.
  • the technical problems of low operating speed and high requirements for equipment hardware have improved the reading efficiency and work efficiency of users.
  • the step of classifying the three-dimensional human body model into several grouped data according to a predetermined classification condition in S100, as shown in FIG. 2, specifically includes:
  • S110 Determine the medical anatomy classification data group of the three-dimensional human body data according to the medical anatomy classification information.
  • S120 Determine the art resource category information corresponding to the medical anatomy system classification, and allocate the art resource data corresponding to the art resource category information in the three-dimensional human body model data to the medical anatomy classification data group to obtain the several grouped data.
  • the medical anatomy classification information includes human body shape classification information, human organ classification information, and human body system classification information.
  • the above-mentioned medical anatomy classification information can also be combined.
  • the data of each human body system can also be grouped (such as sports system grouped data). ) Classified according to the classification information of human organs.
  • a kind of art resource category information is divided according to the form of graphic representation, including two-dimensional resource information and three-dimensional resource information.
  • these grouped data are classified according to the type of information recorded, and include at least three types: human body shape art resource grouping data, human organ art resource grouping data, and human body system art resource grouping data.
  • the head data may include a three-dimensional head image.
  • the three-dimensional head portrait has two-dimensional texture maps with finer skin texture and color elements distributed according to anatomical rules.
  • the grouped data of human body shape art resources may be the two Dimensional map.
  • each type of medical anatomy classification information corresponds to a type of art resource type information.
  • the specific meaning of combining art resource category information is: according to the selected specific medical anatomy classification information, for example, according to the human body system classification information, three-dimensional human body model data is classified into several personal system grouping data, and then for any human body system grouping data, For example, for grouping data of the motion system, it is necessary to determine the art resource data corresponding to the motion system from the original three-dimensional human body model data, that is, the three-dimensional resource and the two-dimensional resource of the motion system.
  • the three-dimensional resource is the skeleton model frame, which is specifically determined by the modeling Provided by software, two-dimensional resources are textures that can be attached to a rich skeleton model frame, such as pictures that can reflect bone material and color.
  • two-dimensional resources are textures that can be attached to a rich skeleton model frame, such as pictures that can reflect bone material and color.
  • the determination of the predetermined classification condition further includes: obtaining human body model data Based on the type information of the operating platform, the art resource data is determined according to the type information.
  • an operating platform that runs the three-dimensional human body model data may be considered.
  • the PC Personal Computer
  • the PC Personal Computer
  • the PC Personal Computer
  • the classification information of human organs can be selected as the medical anatomy classification information to provide a large number of sub-packaged data but a small amount of data in a single data packet.
  • the human body shape classification information or the human body system classification information can be selected as the medical anatomy classification information, but the art resource data with a smaller picture definition is selected correspondingly to ensure that the data volume of each data packet body is within the set range.
  • the repeated resources in the grouped data are determined, and the specific S200 of the grouped data after the repeated resources is removed.
  • S210 According to the public information in the human medical anatomy classification information, extract data related to the public information from the several grouped data and perform deduplication processing to obtain the repeated resources.
  • S220 Delete the data related to the public information from the plurality of grouped data to obtain the sorted grouped data.
  • the public information may include blood vessels, skin, muscles and other local parts.
  • each medical anatomy classification data group such as head grouping data and trunk grouping data
  • the two-dimensional textures of these parts are duplicate resources.
  • the duplicate resources need to be extracted from each grouped data group (at the same time, these extracted duplicate resources are deleted from the original grouped data group) and deduplicated , And then individually packaged into sub-packaged data related to public information.
  • the technical idea of S200 is to analyze the grouped data obtained through S100 one by one to find out the duplicate resources in the grouped data.
  • the duplicated resources may come from two grouped data, or from three grouped data, or all grouped data. Total.
  • One source of repetitive resources is the human body structure or tissue that has a transitional effect on the three-dimensional human body. According to the specific medical anatomy classification information, there are also differences in repetitive resources. Separate the repeated resources and pack them separately, which can reduce the redundancy of each grouped data and facilitate data management.
  • the texture and shape of human skin are mostly the same, such as face skin and abdominal skin, etc.
  • the three-dimensional human body model is grouped according to the body shape classification information to obtain head grouping data and torso grouping data.
  • the texture resources that represent the appearance and texture of the skin are duplicate resources, and there is no need to include the above-mentioned duplicate texture resources in both the head grouping data and the trunk grouping data.
  • the stored S300 includes:
  • Adding user authority information in the process of data packaging operations on packet data can realize orderly management of subpackage data and provide a convenient way for business operations.
  • Users with different user rights download and load sub-packaged data according to their own authorized scope, and use the sub-packaged data in different ways and information viewing ranges.
  • Specific user rights information such as update rights, personalized customization rights, etc.
  • the S300 that packs the repeated resources and each sorted packet data into packet data and stores them respectively includes: transcoding the packet data into binary Packetized data; stores binary packetized data.
  • data will be transmitted in the form of characters, but three-dimensional models are not suitable. Because the data package of three-dimensional models is generally large, the efficiency of transmission in the form of characters is very low, and the binary system avoids the decoding process of characters and makes the data available. It is directly recognized by the processor, so it can greatly improve the efficiency of sub-packaged data loading.
  • the subpackaged data of the three-dimensional human body model is transcoded into a binary file through an editor (for example, a Unity editor), so that the space occupied by the subpackaged data in the server becomes smaller, which is convenient for the client to download quickly. After the client downloads the sub-packaged data of the 3D human body model, it can also be directly read and displayed quickly, avoiding the intermediate translation link.
  • an editor for example, a Unity editor
  • medical anatomy classification information includes at least one of the following: human body shape classification information, human organ classification information, or human body system classification information; art resource classification information includes two-dimensional resources Information and three-dimensional resource information.
  • the data is classified into a number of individual system groupings.
  • the repeated resources are packaged into sub-packaged data, and each sorted grouped data is respectively packaged into sub-packaged data, and the specific method of storing all the packaged data further includes:
  • the subcontracting catalog table includes multiple pieces of mapping information corresponding to the subcontracting data one-to-one; the subcontracting catalog table is stored.
  • the repeated resources of the human body shape and the grouped data of the human body shape after sorting can be determined, that is, the sorted head group data, neck group data, and limb group data, etc. .
  • the repeated resource subcontracting of the human body shape and the human body shape subcontracting data are obtained, such as the subcontracting data of the shared skin, the header part of the package data, the neck subcontracting data, and the limb subcontracting data, etc.
  • the sub-contracted data obtained by S300 has a corresponding relationship with the three-dimensional human body model. All sub-contracted data includes the complete data of the three-dimensional human body model. This corresponding relationship provides an index table for subsequent data management and user reference.
  • the subcontracted data comes from the grouped data, which corresponds to the grouped data one-to-one.
  • the grouped data corresponds to each part of the three-dimensional human body model.
  • a subcontracting catalog table of corresponding mapping information is stored along with the subcontracting data, and the scattered subcontracting data is relinked into a complete whole through the subcontracting catalog table.
  • the subcontracting catalog table can specifically set two index levels, the first level includes the catalog corresponding to the medical anatomy classification information, and the second level includes the catalog corresponding to each subcontracted data in each medical anatomy classification information, so as to facilitate the When there are more medical anatomical classification information, the sub-package data that the user needs can be quickly found.
  • more index levels can be set in the subpackage directory table, and this application is not limited to this.
  • the repeated resources are packaged into sub-packaged data, and each sorted grouped data is respectively packaged into sub-packaged data, and after storing all the packaged data, the method Also includes:
  • the subcontracting catalog table determined according to the organized human system grouping data is displayed.
  • the subcontracting catalog table includes multiple pieces of mapping information corresponding to the subcontracting data of the human body system.
  • the subcontracting data of the human body system includes: sports System subcontracting data, nervous system subcontracting data, endocrine system subcontracting data, circulatory system subcontracting data, respiratory system subcontracting data, digestive system subcontracting data, urinary system subcontracting data and reproductive system subcontracting data;
  • the human body system subcontracting data corresponding to the viewing request is obtained and displayed.
  • the human body system classification information When used to classify the human body three-dimensional model data, it can obtain the grouped data including the motor system grouped data, the grouped data of the nervous system, the grouped data of the endocrine system, the grouped data of the circulatory system, the grouped data of the respiratory system, the grouped data of the digestive system, and the urinary system.
  • Grouping data and reproductive system grouping data of the human body system grouping information and then according to the body system grouping information and related art resource data, respectively to obtain sports system subcontracting data, nervous system subcontracting data, endocrine system subcontracting data, and circulatory system subcontracting data.
  • the device When the device receives a data query instruction, it indicates that the user has issued a query request for 3D human body model information. According to this data query request, the subpackage data is found correspondingly, and the subpackage data is displayed through the relevant display device to realize the user's need for reference The purpose of human body information.
  • the review of sub-packaged data obtained according to other types of classification is similar to this process, and will not be repeated.
  • the embodiment of the second aspect of the present disclosure correspondingly provides a human body model data display method, which specifically includes: in response to a human body data query instruction, obtaining human body model subcontracting data corresponding to the human body data query instruction; the human body model subcontracting data adopts The human body model data optimization method provided in the first aspect of the present disclosure is determined; the respective data is decompressed and the human body model sub-packaged data is displayed.
  • obtaining the subpackage data of the human body model corresponding to the data query instruction specifically includes: in response to the data query instruction, displaying grouping according to the organized human body system
  • the subcontracting catalog table determined by the data, the subcontracting catalog table includes multiple pieces of mapping information that correspond to the subcontracted data of the human body system.
  • the subcontracted data of the human body system includes: subcontracting data of the sports system, subcontracting data of the nervous system, and subcontracting the endocrine system.
  • the human body system subcontracting data corresponding to the viewing request is obtained.
  • the above implementation is a process that is presented by the device according to the user’s data query instruction when the subpackaged data is specifically human body system subpackaged data.
  • the process of displaying specific medical anatomical classification information is the same, and will not be repeated.
  • the above process can be completed on the client side or the server side, or in the combination of the client side and the server side.
  • an APP Application
  • the client displays the subcontracting catalog table (the subcontracting catalog table has an information link with the subcontracting catalog table on the server side), and then according to the user's selection of subcontracting data on the subcontracting catalog table, that is, for the subcontracting catalog table View the request and download the stored sub-package data from the server.
  • S300 determines a subcontracting catalog table of the human body system classification, and sends the viewing request that the user wants to see the motion system to the server, and the server stores the The sub-package data of the motion system is returned to the client, and then downloaded by the client, the required human motion system model can be displayed on the client.
  • the original data collection of the three-dimensional human body model is realized, which mainly includes three aspects: creating art resources, collecting medical data, and collecting platform performance information.
  • the collection of medical data includes at least two aspects, human body partial information and Human body system information, art resources and medical data correspond to each other, and the number of types of medical data to be collected is determined based on platform performance information.
  • the original data of the three-dimensional human body model can be obtained by data fusion.
  • Art resources are created by human body image data collection equipment. For example, an X-ray machine can be used to obtain the state of human bones, and anatomical photos of bones can be obtained by a camera, and then rendered and synthesized by image processing software.
  • Medical data comes from various instruments and databases for obtaining human biological information, and platform performance information can be directly identified by terminal devices or servers with identification chips when communicating with the accessed platform. These raw data can be transmitted to the terminal device or server by communicating with the terminal device or server.
  • the terminal device or the server performs data processing on the acquired raw data of the three-dimensional human body model, and specifically performs data processing through an editor in the device.
  • the content of the data processing is to classify the three-dimensional human body model data into several grouped data according to predetermined classification conditions.
  • the predetermined classification conditions include medical anatomy classification information and art resource category information.
  • Unity3D a software developed by Unity Technologies
  • Unity3D Fully integrated professional game engine
  • the device subcontracts according to the data matrix, and obtains subcontracted data.
  • the data matrix represents the classification information of medical anatomy, the category information of art resources, and the type information of the operating platform.
  • the data matrix is a data processing format of Unity3D, and information such as medical anatomy classification information and art resource category information is specifically represented by a data matrix. After subcontracting, you can get subcontracted data running on multiple platforms, such as android platform package, iOS platform package, PC platform package, etc. Each platform package includes information classified according to one or more medical anatomy The sub-packaged data obtained by classification.
  • the terminal device when the user uses the terminal device, he first touches the relevant application software on the display screen of the terminal device.
  • the application software in the terminal device is opened according to the user's touch operation, and the terminal device loads the scene.
  • Various human-computer interaction interfaces presented on the display screen of the terminal device such as a query interface, where the three-dimensional human body model and its parts are displayed in the query interface; the user's input based on touch, gesture, or voice is input for the displayed three-dimensional human body
  • the selected operation of certain parts of the model confirms that the user’s request for human body model information for these parts is received, the terminal device checks the resource integrity, and judges the integrity of the sub-contracted data corresponding to the submitted query request. If the terminal device is stored If the subcontracted data is available and the resource is complete, the resource is loaded to enter the scene, and the user consults the human body model data on the display screen of the terminal device.
  • the terminal device fails to check the resource integrity, it will determine the resource list downloaded from the server, corresponding to the download user’s query request corresponding to the subpackage data list, the list may be one subpackage data, or it may be multiple subpackages data.
  • the packaged data is downloaded from the server in the form of byte stream or downloaded from the local storage of the terminal device to the cache, and the downloaded resource is decompressed and/or decrypted through the terminal device APP (APPlication, application), and then judge whether The download is completed, if it is completed, that is, "Yes” in Figure 5, then load the resource operation again, if it is not completed, that is, "No” in Figure 5, continue to determine the list of resources that need to be downloaded. After the above process, the user's operation of consulting the three-dimensional human body model is completed.
  • the server provides the sub-package data list corresponding to the above-mentioned query request that the terminal device needs to download according to the human body model information query request generated by the user on the terminal device, and the sub-package data list Send to the terminal device.
  • the embodiment of the third aspect of the present disclosure provides a human body model data processing device 10, as shown in FIG. 6, including a grouping module 11, a sorting module 12, and a packing module 13, wherein:
  • the grouping module 11 is used to obtain three-dimensional human body model data, and classify the three-dimensional human body model data into several grouped data according to predetermined classification conditions.
  • the predetermined classification conditions include medical anatomy classification information and art resource category information;
  • the sorting module 12 is used to determine the repeated resources in the grouped data according to each grouped data, and the sorted grouped data after removing the repeated resources;
  • the packing module 13 is used to pack the repeated resources into sub-packed data, respectively pack the sorted grouped data into sub-packed data, and store all part of the packed data.
  • the human body model data processing device subdivides the complete three-dimensional human body model data into several groups according to the characteristics of medical anatomy classification information and art resource classification information, sorts the grouped data after grouping, and packs them into independent groups.
  • the data is sub-contracted and the complete 3D human body model data is reduced to zero so that users can load the data required by the user according to their needs. There is no need to load all 3D human body data at one time, thus solving the problem of low software running speed when downloading or loading the 3D human body model.
  • the technical problem with high requirements for equipment hardware has improved the reading efficiency and work efficiency of users.
  • the grouping module 11 is further configured to:
  • the medical anatomy classification information determine the medical anatomy classification data group of the three-dimensional human body data
  • the art resource category information corresponding to the medical anatomy system classification is determined, and the art resource data corresponding to the art resource category information in the three-dimensional human body model data is allocated to the medical anatomy classification data group to obtain the several grouped data.
  • the grouping module 11 is further configured to:
  • the sorting module 12 is also used to:
  • the data related to the public information is deleted from the plurality of grouped data to obtain the sorted grouped data.
  • the packaging module 13 is also used to:
  • the packaging module 13 is also used to:
  • the medical anatomy classification information includes at least one of the following: human body shape classification information, human organ classification information, or human body system classification information; art resource classification information includes two-dimensional resource information and Three-dimensional resource information.
  • the packaging module 13 is also used to:
  • packaging module 13 is also used for:
  • the subcontracting catalog table includes multiple pieces of mapping information corresponding to the subcontracting data of the human body system.
  • the subcontracting data of the human body system includes: sports system subcontracting data, nerves System subcontracting data, endocrine system subcontracting data, circulatory system subcontracting data, respiratory system subcontracting data, digestive system subcontracting data, urinary system subcontracting data and reproductive system subcontracting data;
  • the human body system subcontracting data corresponding to the viewing request is obtained and displayed.
  • the electronic device includes a display and further includes a memory and a processor.
  • the memory is electrically connected to the processor.
  • At least one computer program stored in the memory, is used to implement various optional implementations of the human body model data processing method or the human body model data display method provided by the embodiments of the present disclosure when being executed by the processor.
  • the electronic equipment provided by the embodiments of the present disclosure may be specially designed and manufactured for the required purpose, or may also include known equipment in a general-purpose computer. These devices have computer programs stored in them, which are selectively activated or reconfigured. Such a computer program may be stored in a device (for example, computer) readable medium or in any type of medium suitable for storing electronic instructions and respectively coupled to a bus.
  • the user does not need to load all the three-dimensional human body data at one time, thereby solving the technical problems of low software running speed when downloading or loading the three-dimensional human body model and high requirements on the hardware of the device.
  • the present disclosure provides an electronic device in an optional embodiment.
  • the electronic device 2000 shown in FIG. 7 includes a processor 2001 and a memory 2003.
  • the processor 2001 and the memory 2003 are electrically connected, such as connected via a bus 2002.
  • the processor 2001 can be a CPU (Central Processing Unit, central processing unit), a general-purpose processor, DSP (Digital Signal Processor, data signal processor), ASIC (Application Specific Integrated Circuit, application-specific integrated circuit), FPGA (Field-Programmable Gate) Array, field programmable gate array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in conjunction with the present disclosure.
  • the processor 2001 may also be a combination for realizing calculation functions, for example, including a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and so on.
  • the bus 2002 may include a path for transferring information between the above-mentioned components.
  • the bus 2002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus or the like.
  • the bus 2002 can be divided into an address bus, a data bus, a control bus, and so on. For ease of presentation, only one thick line is used to represent in FIG. 7, but it does not mean that there is only one bus or one type of bus.
  • the memory 2003 can be ROM (Read-Only Memory) or other types of static storage devices that can store static information and instructions, RAM (random access memory), or other types that can store information and instructions
  • the dynamic storage device can also be EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read-Only Memory, CD-ROM) or other optical disc storage, optical disc storage ( Including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or can be used to carry or store desired program codes in the form of instructions or data structures and can be stored by a computer Any other media taken, but not limited to this.
  • the electronic device 2000 may further include a transceiver 2004.
  • the transceiver 2004 can be used for signal reception and transmission.
  • the transceiver 2004 may allow the electronic device 2000 to perform wireless or wired communication with other devices to exchange data. It should be noted that the transceiver 2004 is not limited to one in practical applications.
  • the electronic device 2000 may further include an input unit 2005.
  • the input unit 2005 may be used to receive input numbers, characters, images, and/or sound information, or generate key signal inputs related to user settings and function control of the electronic device 2000.
  • the input unit 2005 may include, but is not limited to, one or more of touch screen, physical keyboard, function keys (such as volume control buttons, switch buttons, etc.), trackball, mouse, joystick, camera, sound pickup, etc.
  • the electronic device 2000 may further include an output unit 2006.
  • the output unit 2006 can be used to output or display the information processed by the processor 2001.
  • the output unit 2006 may include, but is not limited to, one or more of a display device, a speaker, a vibration device, and the like.
  • FIG. 7 shows an electronic device 2000 having various devices, it should be understood that it is not required to implement or have all the illustrated devices. It may be implemented alternatively or provided with more or fewer devices.
  • the memory 2003 is used to store application program codes for executing the solutions of the present disclosure, and the processor 2001 controls the execution.
  • the processor 2001 is configured to execute application program codes stored in the memory 2003 to implement any human body model data processing method or any human body model data display method provided in the embodiments of the present disclosure.
  • embodiments of the present disclosure provide a computer-readable storage medium with a computer program stored on the computer-readable storage medium.
  • the program is executed by a processor, any human body provided by the embodiments of the present disclosure Model data processing method or any human body model data display method.
  • the computer-readable storage medium provided by the embodiments of the present disclosure does not need to load all three-dimensional human body data at one time, thereby solving the technical problems of low software running speed when downloading or loading a three-dimensional human body model and high requirements on equipment hardware. , Improve the user's reading efficiency and work efficiency.
  • first and second are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with “first” and “second” may explicitly or implicitly include one or more of these features. In the description of the present disclosure, unless otherwise specified, "plurality” means two or more.
  • each module is only a division of logical functions, and can be fully or partially integrated into one physical entity in actual implementation, or can be physically separated.
  • these modules can all be implemented in the form of software called by processing elements; they can also be implemented in the form of hardware; some modules can be implemented in the form of calling software by processing elements, and some of the modules can be implemented in the form of hardware.
  • the determination module may be a separately established processing element, or it may be integrated into a certain chip of the above-mentioned device for implementation.
  • it may also be stored in the memory of the above-mentioned device in the form of program code, which is determined by a certain processing element of the above-mentioned device.
  • each step of the above method or each of the above modules can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.
  • each module, unit, sub-unit or sub-module may be one or more integrated circuits configured to implement the above method, for example: one or more specific integrated circuits (Application Specific Integrated Circuit, ASIC), or, one or Multiple microprocessors (digital signal processor, DSP), or one or more field programmable gate arrays (Field Programmable Gate Array, FPGA), etc.
  • ASIC Application Specific Integrated Circuit
  • DSP digital signal processor
  • FPGA Field Programmable Gate Array
  • the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processors that can call program codes.
  • CPU central processing unit
  • these modules can be integrated together and implemented in the form of a system-on-a-chip (SOC).
  • SOC system-on-a-chip

Abstract

一种人体模型数据处理方法、装置、电子设备及存储介质,该方法包括:获取三维人体模型数据,根据预定分类条件将三维人体模型数据分类为若干个分组数据,预定分类条件包括医学解剖分类信息和美术资源类别信息(S100);根据各个分组数据,确定分组数据中的重复资源、以及去除重复资源后的整理后分组数据(S200);将重复资源和各整理后分组数据分别打包为分包数据并存储(S300)。

Description

人体模型数据处理方法、装置、电子设备及存储介质
相关申请的交叉引用
本申请主张在2020年6月17日在中国提交的中国专利申请号No.202010556046.7的优先权,其全部内容通过引用包含于此。
技术领域
本公开涉及互联网数据处理技术领域,具体而言,本公开涉及一种人体模型数据处理方法、装置、电子设备及存储介质。
背景技术
随着计算机技术的发展,计算机能够处理的问题越来越复杂,过程中所应用和产生的数据越来越多,得到的处理结果也越来越精细,诸多软件在进行大型场景处理的过程中,经常要加载大量的数据文件,例如基本模型、零件材质、高清贴图和精细特效等不可缺少的数据资源。
例如,在对软件应用场景的高精细的人体三维模型处理过程中,由于人体三维模型存在着很多精确细腻的特性,容易影响这些人体三维模型在软件中的加载。由于人体三维模型具有高精细的特点,因此人体三维模型不仅本身占有着较大的数据空间,还连带着数量巨大并且同时占据数据空间也巨大的贴图文件。
发明内容
第一个方面,本公开提供了一种人体模型数据处理方法,包括:
获取三维人体模型数据,根据预定分类条件将三维人体模型数据分类为若干个分组数据,预定分类条件包括医学解剖分类信息和美术资源类别信息;
根据各个分组数据,确定分组数据中的重复资源、以及去除重复资源后的整理后分组数据;
将重复资源打包为分包数据,将各整理后分组数据分别打包为分包数据,存储全部分包数据。
在第一个方面的某些实现方式中,所述根据预定分类条件将三维人体模型分类为若干个分组数据,包括:
根据医学解剖分类信息,确定三维人体数据的医学解剖分类数据组;
确定与医学解剖系统分类对应的美术资源类别信息,将三维人体模型数据中与所述美术资源类别信息对应的美术资源数据分配到医学解剖分类数据组中,得到若干个分组数据。
在第一个方面的某些实现方式中,
将三维人体模型数据中与所述美术资源类别信息对应的美术资源数据分配到所述医学解剖分类数据组中之前,所述方法还包括:
获取人体模型数据的运行平台的类型信息,根据所述运行平台的类型信息确定所述美术资源数据。
在第一个方面的某些实现方式中,所述根据各个分组数据,确定分组数据中的重复资源,以及去除重复资源后的整理后分组数据包括:
根据人体医学解剖分类信息中的公共信息,从所述若干个分组数据中提取与所述公共信息有关的数据并进行去重处理,得到所述重复资源;
将所述与所述公共信息有关的数据从所述若干个分组数据中删除,得到所述整理后分组数据。
在第一个方面的某些实现方式中,所述美术资源数据包括骨骼模型框架和附着丰富骨骼模型框架的贴图。
在第一个方面的某些实现方式中,所述将重复资源打包为分包数据,将各整理后分组数据分别打包为分包数据,包括:
获取与重复资源和各个整理后分组数据对应的用户权限信息,在分包数据中添加用户权限信息。
在第一个方面的某些实现方式中,所述存储全部分包数据,包括:
将分包数据转码为二进制的分包数据;
存储二进制的分包数据。
在第一个方面的某些实现方式中,医学解剖分类信息包括以下至少一种:人体外形分类信息、人体器官分类信息或人体系统分类信息;美术资源类别信息包括二维资源信息和三维资源信息。
在第一个方面的某些实现方式中,所述将重复资源打包为分包数据,将各整理后分组数据分别打包为分包数据,存储全部分包数据,包括:
根据重复资源和各个整理后分组数据,确定分包目录表,分包目录表包括多条与分包数据一一对应的映射信息;
存储分包目录表。
在第一个方面的某些实现方式中,所述将重复资源打包为分包数据,将各整理后分组数据分别打包为分包数据,存储全部分包数据之后,所述方法还包括:
响应于数据查询指令,
显示根据整理后的人体系统分组数据确定分包目录表,分包目录表包括多条与人体系统分包数据一一对应的映射信息,人体系统分包数据包括:运动系统分包数据、神经系统分包数据、内分泌系统分包数据、循环系统分包数据、呼吸系统分包数据、消化系统分包数据、泌尿系统分包数据和生殖系统分包数据;
响应于针对分包目录表中的一条映射信息的查看请求,获取与查看请求相对应的分包数据并显示。
第二个方面,本公开提供了一种人体模型数据展示方法,包括:
响应于人体数据查询指令,获取与人体数据查询指令对应的人体模型分包数据;人体模型分包数据采用本公开第一个方面提供的人体模型数据优化方法确定;
对所述分别数据进行解压缩处理并显示所述人体模型分包数据。
在第二个方面的某些实现方式中,响应于数据查询指令,获取与数据查询指令对应的人体模型的分包数据,包括:
响应于数据查询指令,获取根据整理后的人体系统分组数据确定的分包目录表并显示所述分包目录表,分包目录表包括多条与人体系统分包数据一一对应的映射信息,人体系统分包数据包括:运动系统分包数据、神经系统分包数据、内分泌系统分包数据、循环系统分包数据、呼吸系统分包数据、消化系统分包数据、泌尿系统分包数据和生殖系统分包数据;
响应于针对分包目录表中的一条映射信息的查看请求,获取与查看请求 相对应的人体系统分包数据。
第三个方面,本公开提供了一种人体模型数据处理装置,包括:
分组模块,用于获取三维人体模型数据,根据预定分类条件将三维人体模型数据分类为若干个分组数据,预定分类条件包括医学解剖分类信息和美术资源类别信息;
整理模块,用于根据各个分组数据,确定分组数据中的重复资源,以及去除重复资源后的整理后分组数据;
打包模块,用于将重复资源打包为分包数据,将各整理后分组数据分别打包为分包数据,存储全部分包数据。
第四个方面,本公开提供了一种电子设备,包括显示器,还包括:
处理器;
存储器,与处理器电连接;
至少一个程序,被存储在存储器中并被配置为由处理器执行,至少一个程序被配置用于:实现如本公开第一个方面描述的人体模型数据处理方法或如第二方面描述的人体模型数据展示方法。
第五个方面,本公开提供了一种计算机可读存储介质,计算机可读存储介质存储有至少一条指令、至少一段程序、代码集或指令集,至少一条指令、至少一段程序、代码集或指令集由处理器加载并执行以实现如本公开第一个方面描述的人体模型数据处理方法或如第二方面描述的人体模型数据展示方法。
本公开附加的方面和优点将在下面的描述中部分给出,这些将从下面的描述中变得明显,或通过本公开的实践了解到。
附图说明
本公开上述的和/或附加的方面和优点从下面结合附图对实施例的描述中将变得明显和容易理解,其中:
图1为本公开实施例提供的一种人体模型数据处理方法的流程示意图;
图2为本公开实施例提供的根据预定分类条件将三维人体模型分类为若干个分组数据的流程示意图;
图3为本公开实施例提供的根据各个分组数据,确定分组数据中的重复资源,以及去除重复资源后的整理后分组数据的流程示意图;
图4为本公开一个实例提供的一种人体模型数据处理方法的流程示意图;
图5为本公开一个人体模型数据查询实例的流程图;
图6为本公开实施例提供的一种人体模型数据处理装置的结构的框架示意图;
图7为本公开实施例提供的一种人体模型数据处理的电子设备的结构的框架示意图。
具体实施方式
下面详细描述本公开,本公开的实施例的示例在附图中示出,其中自始至终相同或类似的标号表示相同或类似的部件或具有相同或类似功能的部件。此外,如果已知技术的详细描述对于示出的本公开的特征是不必要的,则将其省略。下面通过参考附图描述的实施例是示例性的,仅用于解释本公开,而不能解释为对本公开的限制。
本技术领域技术人员可以理解,除非另外定义,这里使用的所有术语(包括技术术语和科学术语),具有与本公开所属领域中的普通技术人员的一般理解相同的意义。还应该理解的是,诸如通用字典中定义的那些术语,应该被理解为具有与相关技术的上下文中的意义一致的意义,并且除非像这里一样被特定定义,否则不会用理想化或过于正式的含义来解释。
本技术领域技术人员可以理解,除非特意声明,这里使用的单数形式“一”、“一个”、“所述”和“该”也可包括复数形式。应该进一步理解的是,本公开的说明书中使用的措辞“包括”是指存在所述特征、整数、步骤、操作、元件和/或组件,但是并不排除存在或添加一个或多个其他特征、整数、步骤、操作、元件、组件和/或它们的组。应该理解,当我们称元件被“连接”或“耦接”到另一元件时,它可以直接连接或耦接到其他元件,或者也可以存在中间元件。此外,这里使用的“连接”或“耦接”可以包括无线连接或无线耦接。这里使用的措辞“和/或”包括一个或更多个相关联的列出项的全部或任一单元和全部组合。
随着人们对数据处理结果要求的更加精细化,经常要加载大量的数据文 件,除非具有较为充足的硬件储备,否则很难满足目前对大规模数据处理对象的快速加载和运行处理要求。
另外,相关技术中进行人体三维模型的展示或编辑需要调用或加载的数据文件较多,软件运行速率慢,还对计算机硬件有较高的要求,也容易产生因为用户长时间等待软件运行而工作效率低下的问题。
本公开提供的人体模型数据处理方法、装置、电子设备及存储介质,旨在解决相关技术的如上技术问题。
下面以具体地实施例对本公开的技术方案以及本公开的技术方案如何解决上述技术问题进行详细说明。
本公开第一个方面的实施例中提供了一种人体模型数据处理方法,如图1所示,包括下列步骤:
S100:获取三维人体模型数据,根据预定分类条件将三维人体模型数据分类为若干个分组数据,预定分类条件包括医学解剖分类信息和美术资源类别信息。
S200:根据各个分组数据,确定分组数据中的重复资源、以及去除重复资源后的整理后分组数据。
S300:将重复资源打包为分包数据,将各整理后分组数据分别打包为分包数据,存储全部分包数据。
在S100中,设备获取到三维人体模型数据,本公开中该三维人体模型数据是通过外界输入的原始数据,此处的设备可以为终端设备,也可以是服务器。经S100完成对三维人体模型数据的初步分类后,在S200中,对这些分类后的数据进行去重处理,通过将分组数据中冗余的重复资源进行整理,避免出现资源冗余的现象,使数据的分组更加清晰,便于进行数据管理。经S200获取到分组清晰的分组数据后,再通过S300以数据打包操作将这些分组数据打包为分包数据,完整的三维人体模型数据由若干个分包数据组成,这些分包数据相互联系又彼此独立,可供用户择取其中之一或若干个加载运行。
本公开提供的人体模型数据处理方法,通过将完整的三维人体模型数据按照医学解剖分类信息和美术资源类别信息的特点细分为若干组,对分组后的分组数据进行整理去重,打包为独立的分包数据,将完整的三维人体模型 数据化整为零,以便于用户根据需要加载用户需要的数据,而无需一次加载全部的三维人体数据,从而解决了下载或加载人体三维模型时,软件运行速率低,对设备硬件要求高的技术问题,提高了用户的阅读效率和工作效率。
可选地,在上述实施例的一种实现方式中,S100中根据预定分类条件将三维人体模型分类为若干个分组数据的步骤,如图2所示,具体包括:
S110:根据医学解剖分类信息,确定三维人体数据的医学解剖分类数据组。
S120:确定与医学解剖系统分类对应的美术资源类别信息,将三维人体模型数据中与所述美术资源类别信息对应的美术资源数据分配到医学解剖分类数据组中,得到所述若干个分组数据。
由于对人体结构分类的方式有很多,在某些可选的实现方式中,医学解剖分类信息包括人体外形分类信息、人体器官分类信息和人体系统分类信息。在一些实施例中,上述各医学解剖分类信息还可以进行组合,例如,在对三维人体模型数据根据人体系统分类信息进行分类后,进一步,还可以对各人体系统分组数据(如运动系统分组数据)按照人体器官分类信息进行分类。一种美术资源类别信息按照图形表现形式进行划分,包括二维资源信息和三维资源信息。
根据医学解剖分类信息获取到三维人体数据的医学解剖分类数据组之后,再将三维人体数据中与医学解剖分类数据组对应的美术资源类别信息对应的数据分组,将二者结合,获得包含医学解剖分类数据组和相应美术资源类别信息的分组数据。
即这些分组数据按照所记载的信息内容种类划分,包括至少三种:人体外形美术资源分组数据、人体器官美术资源分组数据和人体系统美术资源分组数据。例如头部数据中可以包括三维头部图像,该三维头部头像上按照解剖学的规律分布有较为精细的皮肤质地和颜色等元素的二维贴图,人体外形美术资源分组数据可以是所述二维贴图。
当某些用户只需要前述三种医学解剖分类信息中的一种,例如,人体外形分类信息,则可以根据人体外形分类信息划分出多个分组数据,例如头部分组数据、脖颈分组数据和四肢分组数据等。而如果需要按照人体器官分类 信息进行分类,则得到心脏分组数据、眼睛分组数据、耳朵分组数据和肝脏分组数据等。实际上,每种医学解剖分类信息都对应着一种美术资源类别信息。
结合美术资源类别信息的含义具体为:根据选择的具体医学解剖分类信息,例如,根据人体系统分类信息对三维人体模型数据分类为若干个人体系统分组数据,之后,对于任一人体系统分组数据,例如,运动系统分组数据,需要在原始三维人体模型数据确定出与运动系统相对应的美术资源数据,也即运动系统的三维资源和二维资源,三维资源即是骨骼模型框架,具体由建模软件提供,二维资源则是能够附着丰富骨骼模型框架的贴图,例如能够体现骨骼材质、颜色的图片。美术资源数据中的三维资源与二维资源之间也存在对应关系,三维资源所构成的立体模型框架需要由对应的二维资源填充。
可选地,在上述实施例的另一种实现方式中,S100中的根据预定分类条件将三维人体模型数据分类为若干个分组数据的步骤中,预定分类条件的确定还包括:获取人体模型数据的运行平台的类型信息,根据类型信息确定美术资源数据。
对三维人体模型数据进行分类还需要考虑将要运行三维人体模型数据的运行平台,因为运行平台的应用场景不同、硬件性能不同,为了保证三维人体模型数据的运行顺畅,还应当将运行平台的类型作为预定分类条件之一,制定个性化的分类策略。在一些实施例中,可以在确定美术资源数据时,考虑运行三维人体模型数据的运行平台。
一般地,PC(Personal Computer,个人计算机)端的性能较好,加载数据包的能力较强,所以能够采用更丰富的三维人体模型数据分类方式,而一般移动终端通常需要依靠移动运营商提供的数据流量下载数据包,因此为确保用户快速查阅三维人体模型上的信息,不宜采用较大的数据包体,例如单个数据包体不宜超过20M。例如,在运行平台的类型为移动终端时,可选择以人体器官分类信息作为医学解剖分类信息,提供数量较多但单个数据包体数据量小的分包数据。或者,可以选择人体外形分类信息或人体系统分类信息作为医学解剖分类信息,但对应选择图片清晰度较小的美术资源数据,确保每个数据包体的数据量在设定范围内。
在对软件应用场景的高精细的人体三维模型处理的过程中,随着人们对人体数据采集的精细化,要将人体用更精细逼真的三维模型模拟出来,供人们了解人体状况或者进行医学分析,也就要求有更多的人体结构信息文件以及对应的更真实细腻的贴图文件。这些文件数据占有着巨大的数据空间。另外,在对人体三维模型进行ab(AssetBundles,资源束)包打包操作的时候,由于模型贴图可能存在的重复使用,使得在进行ab包打包时产生极大的贴图冗余现象,进一步增大整个三维人体模型数据的规模,增加软件下载和加载的负担,同时,软件中调用单一巨大的ab包也会影响软件的正常使用。
因此,在本公开上述实施例的又一些可选的实现方式中,如图3所示,根据各个分组数据,确定分组数据中的重复资源,以及去除重复资源后的整理后分组数据的S200具体包括:
S210:根据人体医学解剖分类信息中的公共信息,从所述若干个分组数据中提取与所述公共信息有关的数据并进行去重处理,得到所述重复资源。
S220:将所述与所述公共信息有关的数据从所述若干个分组数据中删除,得到所述整理后分组数据。
在一些实施例中,所述公共信息可以包括血管、皮肤、肌肉等局部部位,各医学解剖分类数据组中,如头部分组数据和躯干分组数据,都可能存在血管、皮肤、肌肉等部位的二维贴图,这些部位的二维贴图即是重复资源,需要将重复资源从各分组数据组中提取出来(同时,将这些提取出来的重复资源从原分组数据组中删除)并进行去重处理,之后单独打包成为有关公共信息的分包数据。
S200的技术思路是先逐一分析经S100得到的分组数据,找出分组数据中存在的重复资源,重复资源可能来源于两个分组数据,也可能来源于三个分组数据,也可能全部分组数据都共有。重复资源的一种来源是三维人体上具有过渡作用的人体结构或组织,根据具体采用的医学解剖分类信息不同,重复资源也存在差异。将重复资源单独区分出来并单独打包,能够减少各个分组数据的冗余度,便于进行数据管理。
举例而言,人体皮肤的质地和外形大部分是相同的,例如脸部的皮肤和腹部皮肤等等,如将三维人体模型按照人体外形分类信息进行分组,得到头 部分组数据和躯干分组数据,表现皮肤外形和质地的贴图资源就是重复资源,无需使头部分组数据和躯干分组数据中都包括上述的重复的贴图资源。
将三维人体模型数据按照用户需求分类成若干组分组数据并进行整理之后,本公开的实施例还提供了一种可选的实现方式,将重复资源和各个整理后分组数据分别打包为分包数据并存储的S300,具体包括:
获取与重复资源和各个整理后分组数据对应的用户权限信息,在分包数据中添加用户权限信息。
在对分组数据进行数据打包操作的过程中增加用户权限信息,能够实现对分包数据的有序管理,提供一种商业运营的便利途径。具有不同用户权限的用户根据其自身得到的授权范围下载和加载分包数据,以不同的方式和信息查阅范围使用分包数据,具体的用户权限信息例如更新权限、个性化定制权限等。
可选地,在本公开的实施例中提供了另一种实现方式,将重复资源和各个整理后分组数据分别打包为分包数据并存储的S300,包括:将分包数据转码为二进制的分包数据;存储二进制的分包数据。
通常来说,数据会以字符的形式传递,但是不适用三维模型,由于三维模型的数据包体一般较大,以字符的形式传递效率很低,而二进制避免了字符的解码过程,使得数据可以直接被处理器识别,因此能够大幅提高分包数据加载效率。具体而言,将三维人体模型的分包数据通过编辑器(例如Unity编辑器)转码成二进制文件,使得分包数据在服务器中的空间占比变小,便于客户端快速下载。客户端下载三维人体模型的分包数据后,也可以快速地直接读取并展示,避免了中间的转译环节。
需要说明的是,在本公开的一个可选的实现方式中,医学解剖分类信息包括以下至少一种:人体外形分类信息、人体器官分类信息或人体系统分类信息;美术资源类别信息包括二维资源信息和三维资源信息。
在一些实施例中,可以
根据人体外形分类信息将三维人体模型数据分类为若干个人体外形分组数据,或者根据人体器官分类信息将三维人体模型数据分类为若干个人体器官分组数据,或者根据人体外形分类信息将三维人体模型数据分类为若干个 人体系统分组数据。
在一些实施例中,上述步骤S300中,将重复资源打包为分包数据,将各整理后分组数据分别打包为分包数据,存储全部分包数据的具体方法,还包括:
根据重复资源和各个整理后分组数据,确定分包目录表,分包目录表包括多条与分包数据一一对应的映射信息;存储分包目录表。
为便于理解本公开人体模型数据处理方法,现描述一种具体案例:
当将人体三维模型数据按照人体外形分类信息进行分类,根据S200,能够确定得人体外形的重复资源、整理后人体外形分组数据,即整理后的头部分组数据、脖颈分组数据和四肢分组数据等。再经S300,得到人体外形的重复资源分包和人体外形分包数据,如共用皮肤的分包数据、头部分包数据、脖颈分包数据和四肢分包数据等。经S300得到的分包数据与三维人体模型具有对应关系,全部的分包数据即包括了三维人体模型的完整数据,这一对应关系为后续数据管理以及用户查阅使用提供了索引表。
分包数据来自于分组数据,与分组数据一一对应,分组数据与三维人体模型的各个部分一一对应,分包数据的数量即为分包目录表中映射信息的条数,将包括这些一一对应的映射信息的分包目录表跟随分包数据一同存储,通过分包目录表将分散的分包数据重新联系为一个完整的整体。分包目录表可具体设置两个索引层级,第一层级包括与医学解剖分类信息相对应的目录,第二层级则包括每种医学解剖分类信息中的各个分包数据对应的目录,以便于在采用的医学解剖分类信息较多的情况下,快速找到用户需要的分包数据。当然,所述分包目录表还可以设置更多索引层级,本申请并不限定于此。
可选地,在上述实现方式的某些具体实施方式中,所述将重复资源打包为分包数据,将各整理后分组数据分别打包为分包数据,存储全部分包数据之后,所述方法还包括:
响应于数据查询指令,显示根据整理后的人体系统分组数据确定的分包目录表,分包目录表包括多条与人体系统分包数据一一对应的映射信息,人体系统分包数据包括:运动系统分包数据、神经系统分包数据、内分泌系统分包数据、循环系统分包数据、呼吸系统分包数据、消化系统分包数据、泌尿 系统分包数据和生殖系统分包数据;
响应于针对分包目录表中的一条映射信息的查看请求,获取与查看请求相对应的人体系统分包数据并显示。
当采用人体系统分类信息对人体三维模型数据进行分类时,能够获得包括运动系统分组数据、神经系统分组数据、内分泌系统分组数据、循环系统分组数据、呼吸系统分组数据、消化系统分组数据、泌尿系统分组数据和生殖系统分组数据的人体系统分组信息,进而根据人体系统分组信息以及相关的美术资源数据,分别得到运动系统分包数据、神经系统分包数据、内分泌系统分包数据、循环系统分包数据、呼吸系统分包数据、消化系统分包数据、泌尿系统分包数据和生殖系统分包数据,以及人体系统重复资源分包数据。
当设备接收到数据查询指令,表明用户发出了三维人体模型信息的查询需求,根据这一数据查询需求对应找到分包数据,并通过相关的显示设备将分包数据显示出来,实现用户查阅所需人体信息的目的。
例如用户想要在手机上查阅运动系统相关信息,打开手机上相关应用软件,当显示在应用软件显示界面上的人体外形分类信息、人体器官分类信息和人体系统分类信息中人体系统分类信息被选中,则运动系统分包数据、神经系统分包数据、内分泌系统分包数据、循环系统分包数据、呼吸系统分包数据、消化系统分包数据、泌尿系统分包数据和生殖系统分包数据对应的分包目录表显示在显示界面上,用户选择运动系统分包数据,手机相应调出运动系统分包数据对应的人体三维模型数据并显示。按照其他类型分类得到的分包数据的查阅与此过程类似,不再赘述。
本公开第二个方面的实施例相应提供了一种人体模型数据展示方法,具体包括:响应于人体数据查询指令,获取与人体数据查询指令对应的人体模型分包数据;人体模型分包数据采用本公开第一个方面提供的人体模型数据优化方法确定;对所述分别数据进行解压缩处理并显示人体模型分包数据。
可选地,在一种具体的实现方式中,响应于数据查询指令,获取与数据查询指令对应的人体模型的分包数据,具体包括:响应于数据查询指令,显示根据整理后的人体系统分组数据确定的分包目录表,分包目录表包括多条与人体系统分包数据一一对应的映射信息,人体系统分包数据包括:运动系 统分包数据、神经系统分包数据、内分泌系统分包数据、循环系统分包数据、呼吸系统分包数据、消化系统分包数据、泌尿系统分包数据和生殖系统分包数据。响应于针对分包目录表中的一条映射信息的查看请求,获取与查看请求相对应的人体系统分包数据。
上述实现方式是当分包数据具体为人体系统分包数据时,被设备根据用户的数据查询指令而呈现出来的过程,对于其他种类的分包数据,具体对于人体外形分类信息和人体器官分类信息,根据与之相应的用户的数据查询指令,展现具体医学解剖分类信息的过程与此相同,不再赘述。
另外,上述过程可在客户端或者服务器端完成,也可在客户端与服务器端结合的情况下完成,例如在客户端部署人体三维模型显示的APP(Application,应用程序),根据客户需求,在客户端显示分包目录表(该分包目录表与服务器端的分包目录表建有信息链接),然后根据用户在分包目录表上对分包数据的选择,也即针对分包目录表的查看请求,从服务器下载其存储的分包数据。具体例如,当用户想要看到的人体系统的运动系统时,经S300确定一人体系统分类的分包目录表,将用户想要看到运动系统的查看请求,发送给服务器,服务器将存储的运动系统分包数据返回给客户端,然后由客户端下载后就可以在客户端上展示所需的人体运动系统模型。
为更方便地理解本公开人体模型数据处理的全过程,下面描述一种实现的实际案例:
如图4所示,首先实现三维人体模型的原始数据收集,主要包括三个方面内容:创建美术资源、收集医学数据以及收集平台性能信息,其中收集医学数据至少包括两个方面,人体局部信息和人体系统信息,美术资源与医学数据相互对应,同时根据平台性能信息决定医学数据的收集种类数。收集上述的数据后,进行数据融合即可得到三维人体模型的原始数据。美术资源是由人体影像资料收集设备创建得到的,例如可选用X光机获取人体骨骼状态,通过摄像机获取解剖后的骨骼照片,再通过图像处理软件渲染合成得到。医学数据来源于各种获取人体生物信息的仪器以及数据库等,而平台性能信息则可直接由带有识别芯片的终端设备或服务器在与接入的平台通信时识别得到。这些原始数据可通过与终端设备或者服务器通信的方式,传输到终端设 备或服务器中。
终端设备或者服务器对获取到的三维人体模型的原始数据进行数据处理,具体通过设备中的编辑器进行数据处理。该数据处理的内容是根据预定分类条件将三维人体模型数据分类为若干个分组数据,其中的预定分类条件包括医学解剖分类信息和美术资源类别信息,例如可采用Unity3D(由Unity Technologies公司开发的一个全面整合的专业游戏引擎)中的Unity编辑器进行,设备根据数据矩阵进行分包,获得分包数据,该过程中数据矩阵表示由医学解剖分类信息、美术资源类别信息和运行平台的类型信息三个要素组成的预定分类条件,数据矩阵是Unity3D的一种数据处理格式,医学解剖分类信息和美术资源类别信息等信息具体采用数据矩阵的方式表示。经分包后,能够得到在多个平台运行的分包数据,例如android(安卓)平台包、iOS平台包和PC平台包等,每个平台包当中包括按照一种或多种医学解剖分类信息分类得到的分包数据。
如图5所示,用户在终端设备上使用时,首先点触终端设备显示屏幕上的有关应用软件,终端设备中的应用软件根据用户的点触操作被开启,终端设备载入场景,即在终端设备的显示屏幕上呈现的各种人机交互界面,例如查询界面,在查询界面中显示三维人体模型及其各部分;接收用户基于触摸、手势或语音等方式输入的针对所显示的三维人体模型某一些部分的选定操作,确认接收到用户针对这些部分的人体模型信息查阅请求,终端设备检查资源完整性,对提交的查阅请求对应的分包数据完整性进行评判,如果终端设备中存有该分包数据且资源完整,则加载资源从而进入场景,用户在终端设备的显示屏上查阅人体模型数据。
而如果终端设备检查资源完整性失败,则确定将从服务器中下载的资源列表,对应下载用户的查阅请求对应的分包数据列表,列表中可能是一个分包数据,也可能是多个分包数据。分包数据以字节流的形式从服务器下载或者从终端设备本地的存储器中下载至缓存,经过终端设备APP(APPlication,应用程序)对下载的资源进行解压操作和/或解密操作,然后判断是否完成下载,如果完成,即图5中的“是”,则再次进行加载资源操作,如果未完成,即图5中的“否”,则继续确定需要下载的资源列表。经过上述过程,完成用 户查阅三维人体模型的操作。
在上述过程中,如果需要服务器的参与,服务器则根据用户在终端设备上产生的人体模型信息查阅请求,提供终端设备所需要下载的上述查阅请求对应的分包数据列表,将该分包数据列表发送到终端设备上。
本公开第三个方面的实施例提供一种人体模型数据处理装置10,如图6所示,包括分组模块11、整理模块12和打包模块13,其中:
分组模块11用于获取三维人体模型数据,根据预定分类条件将三维人体模型数据分类为若干个分组数据,预定分类条件包括医学解剖分类信息和美术资源类别信息;
整理模块12用于根据各个分组数据,确定分组数据中的重复资源,以及去除重复资源后的整理后分组数据;
打包模块13用于将重复资源打包为分包数据,将各整理后分组数据分别打包为分包数据,存储全部分包数据。
本公开提供的人体模型数据处理装置,将完整的三维人体模型数据按照医学解剖分类信息和美术资源类别信息的特点细分为若干组,对分组后的分组数据进行整理去重,打包为独立的分包数据,将完整的三维人体模型数据化整为零,以便于用户根据需要加载用户需要的数据,无需一次加载全部的三维人体数据,从而解决了下载或加载人体三维模型时软件运行速率低,对设备硬件要求高的技术问题,提高了用户的阅读效率和工作效率。
可选地,在上述实施例的一些实现方式中,分组模块11还用于:
根据医学解剖分类信息,确定三维人体数据的医学解剖分类数据组;
确定与医学解剖系统分类对应的美术资源类别信息,将三维人体模型数据中与所述美术资源类别信息对应的美术资源数据分配到医学解剖分类数据组中,得到所述若干个分组数据。
可选地,在上述实施例的一些实现方式中,分组模块11还用于:
获取人体模型数据的运行平台的类型信息,根据运行平台的类型信息确定美术资源数据。
可选地,在上述实施例的另一些实现方式中,整理模块12还用于:
根据人体医学解剖分类信息中的公共信息,从所述若干个分组数据中提 取与所述公共信息有关的数据并进行去重处理,得到所述重复资源;
将所述与所述公共信息有关的数据从所述若干个分组数据中删除,得到所述整理后分组数据。
可选地,在上述实施例的一些实现方式中,打包模块13还用于:
获取与重复资源和各个整理后分组数据对应的用户权限信息,在分包数据中添加用户权限信息。
可选地,在上述实施例的另一些实现方式中,打包模块13还用于:
将分包数据转码为二进制的分包数据;
存储二进制的分包数据。
可选地,在上述实施例的又一些实现方式中,医学解剖分类信息包括以下至少一种:人体外形分类信息、人体器官分类信息或人体系统分类信息;美术资源类别信息包括二维资源信息和三维资源信息。
打包模块13还用于:
根据重复资源和各个整理后分组数据,确定分包目录表,分包目录表包括多条与分包数据一一对应的映射信息;
存储分包目录表。
在上述实现方式中存在一种具体的实施方式,打包模块13还用于:
响应于数据查询指令,
显示根据整理后的人体系统分组数据确定的分包目录表,分包目录表包括多条与人体系统分包数据一一对应的映射信息,人体系统分包数据包括:运动系统分包数据、神经系统分包数据、内分泌系统分包数据、循环系统分包数据、呼吸系统分包数据、消化系统分包数据、泌尿系统分包数据和生殖系统分包数据;
响应于针对分包目录表中的一条映射信息的查看请求,获取与查看请求相对应的人体系统分包数据并显示。
基于同一发明构思,本公开实施例提供了一种电子设备,该电子设备,包括显示器,还包括:存储器和处理器。
存储器与处理器电连接。
至少一个计算机程序,存储于存储器中,用于被处理器执行时,实现本 公开实施例提供的人体模型数据处理方法或人体模型数据展示方法的各种可选实施方式。
本技术领域技术人员可以理解,本公开实施例提供的电子设备可以为所需的目的而专门设计和制造,或者也可以包括通用计算机中的已知设备。这些设备具有存储在其内的计算机程序,这些计算机程序选择性地激活或重构。这样的计算机程序可以被存储在设备(例如,计算机)可读介质中或者存储在适于存储电子指令并分别耦联到总线的任何类型的介质中。
与相关技术相比,通过本公开提供的电子设备,用户无需一次加载全部的三维人体数据,从而解决了下载或加载人体三维模型时软件运行速率低,对设备硬件要求高的技术问题,提高了用户的阅读效率和工作效率。
本公开在一个可选实施例中提供了一种电子设备,如图7所示,图7所示的电子设备2000包括:处理器2001和存储器2003。其中,处理器2001和存储器2003相电连接,如通过总线2002相连。
处理器2001可以是CPU(Central Processing Unit,中央处理器),通用处理器,DSP(Digital Signal Processor,数据信号处理器),ASIC(Application Specific Integrated Circuit,专用集成电路),FPGA(Field-Programmable Gate Array,现场可编程门阵列)或者其他可编程逻辑器件、晶体管逻辑器件、硬件部件或者其任意组合。其可以实现或执行结合本公开公开内容所描述的各种示例性的逻辑方框,模块和电路。处理器2001也可以是实现计算功能的组合,例如包含一个或多个微处理器组合,DSP和微处理器的组合等。
总线2002可包括一通路,在上述组件之间传送信息。总线2002可以是PCI(Peripheral Component Interconnect,外设部件互连标准)总线或EISA(Extended Industry Standard Architecture,扩展工业标准结构)总线等。总线2002可以分为地址总线、数据总线、控制总线等。为便于表示,图7中仅用一条粗线表示,但并不表示仅有一根总线或一种类型的总线。
存储器2003可以是ROM(Read-Only Memory,只读存储器)或可存储静态信息和指令的其他类型的静态存储设备,RAM(random access memory,随机存取存储器)或者可存储信息和指令的其他类型的动态存储设备,也可以是EEPROM(Electrically Erasable Programmable Read Only Memory,电可 擦可编程只读存储器)、CD-ROM(Compact Disc Read-Only Memory,只读光盘)或其他光盘存储、光碟存储(包括压缩光碟、激光碟、光碟、数字通用光碟、蓝光光碟等)、磁盘存储介质或者其他磁存储设备、或者能够用于携带或存储具有指令或数据结构形式的期望的程序代码并能够由计算机存取的任何其他介质,但不限于此。
可选地,电子设备2000还可以包括收发器2004。收发器2004可用于信号的接收和发送。收发器2004可以允许电子设备2000与其他设备进行无线或有线通信以交换数据。需要说明的是,实际应用中收发器2004不限于一个。
可选地,电子设备2000还可以包括输入单元2005。输入单元2005可用于接收输入的数字、字符、图像和/或声音信息,或者产生与电子设备2000的用户设置以及功能控制有关的键信号输入。输入单元2005可以包括但不限于触摸屏、物理键盘、功能键(比如音量控制按键、开关按键等)、轨迹球、鼠标、操作杆、拍摄装置、拾音器等中的一种或多种。
可选地,电子设备2000还可以包括输出单元2006。输出单元2006可用于输出或展示经过处理器2001处理的信息。输出单元2006可以包括但不限于显示装置、扬声器、振动装置等中的一种或多种。
虽然图7示出了具有各种装置的电子设备2000,但是应理解的是,并不要求实施或具备所有示出的装置。可以替代地实施或具备更多或更少的装置。
可选的,存储器2003用于存储执行本公开方案的应用程序代码,并由处理器2001来控制执行。处理器2001用于执行存储器2003中存储的应用程序代码,以实现本公开实施例提供的任一种人体模型数据处理方法或任一人体模型数据展示方法。
基于同一的发明构思,本公开实施例提供了一种计算机可读存储介质,该计算机可读存储介质上存储有计算机程序,该程序被处理器执行时实现本公开实施例所提供的任一人体模型数据处理方法或任一人体模型数据展示方法。
本公开实施例提供的计算机可读存储介质,与相关技术相比,无需一次加载全部的三维人体数据,从而解决了下载或加载人体三维模型时软件运行速率低,对设备硬件要求高的技术问题,提高了用户的阅读效率和工作效率。
本技术领域技术人员可以理解,本公开中已经讨论过的各种操作、方法、流程中的步骤、措施、方案可以被交替、更改、组合或删除。进一步地,具有本公开中已经讨论过的各种操作、方法、流程中的其他步骤、措施、方案也可以被交替、更改、重排、分解、组合或删除。进一步地,相关技术中的具有与本公开中公开的各种操作、方法、流程中的步骤、措施、方案也可以被交替、更改、重排、分解、组合或删除。
术语“第一”、“第二”仅用于描述目的,而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此,限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征。在本公开的描述中,除非另有说明,“多个”的含义是两个或两个以上。
应该理解的是,虽然附图的流程图中的各个步骤按照箭头的指示依次显示,但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明,这些步骤的执行并没有严格的顺序限制,其可以以其他的顺序执行。而且,附图的流程图中的至少一部分步骤可以包括多个子步骤或者多个阶段,这些子步骤或者阶段并不必然是在同一时刻执行完成,而是可以在不同的时刻执行,其执行顺序也不必然是依次进行,而是可以与其他步骤或者其他步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
需要说明的是,应理解以上各个模块的划分仅仅是一种逻辑功能的划分,实际实现时可以全部或部分集成到一个物理实体上,也可以物理上分开。且这些模块可以全部以软件通过处理元件调用的形式实现;也可以全部以硬件的形式实现;还可以部分模块通过处理元件调用软件的形式实现,部分模块通过硬件的形式实现。例如,确定模块可以为单独设立的处理元件,也可以集成在上述装置的某一个芯片中实现,此外,也可以以程序代码的形式存储于上述装置的存储器中,由上述装置的某一个处理元件调用并执行以上确定模块的功能。其它模块的实现与之类似。此外这些模块全部或部分可以集成在一起,也可以独立实现。这里所述的处理元件可以是一种集成电路,具有信号的处理能力。在实现过程中,上述方法的各步骤或以上各个模块可以通过处理器元件中的硬件的集成逻辑电路或者软件形式的指令完成。
例如,各个模块、单元、子单元或子模块可以是被配置成实施以上方法 的一个或多个集成电路,例如:一个或多个特定集成电路(Application Specific Integrated Circuit,ASIC),或,一个或多个微处理器(digital signal processor,DSP),或,一个或者多个现场可编程门阵列(Field Programmable Gate Array,FPGA)等。再如,当以上某个模块通过处理元件调度程序代码的形式实现时,该处理元件可以是通用处理器,例如中央处理器(Central Processing Unit,CPU)或其它可以调用程序代码的处理器。再如,这些模块可以集成在一起,以片上系统(system-on-a-chip,SOC)的形式实现。
本公开的说明书和权利要求书中的术语“第一”、“第二”等是用于区别类似的对象,而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换,以便这里描述的本公开的实施例,例如除了在这里图示或描述的那些以外的顺序实施。此外,术语“包括”和“具有”以及他们的任何变形,意图在于覆盖不排他的包含,例如,包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元,而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。此外,说明书以及权利要求中使用“和/或”表示所连接对象的至少其中之一,例如A和/或B和/或C,表示包含单独A,单独B,单独C,以及A和B都存在,B和C都存在,A和C都存在,以及A、B和C都存在的7种情况。类似地,本说明书以及权利要求中使用“A和B中的至少一个”应理解为“单独A,单独B,或A和B都存在”。
以上仅是本公开的部分实施方式,应当指出,对于本技术领域的普通技术人员来说,在不脱离本公开原理的前提下,还可以做出若干改进和润饰,这些改进和润饰也应视为本公开的保护范围。

Claims (15)

  1. 一种人体模型数据处理方法,包括:
    获取三维人体模型数据,根据预定分类条件将三维人体模型数据分类为若干个分组数据,所述预定分类条件包括医学解剖分类信息和美术资源类别信息;
    根据各个所述分组数据,确定所述分组数据中的重复资源、以及去除所述重复资源后的整理后分组数据;
    将所述重复资源打包为分包数据,将各所述整理后分组数据分别打包为分包数据,存储全部所述分包数据。
  2. 根据权利要求1所述的人体模型数据处理方法,其中,所述根据预定分类条件将三维人体模型分类为若干个分组数据,包括:
    根据所述医学解剖分类信息,确定所述三维人体数据的医学解剖分类数据组;
    确定与医学解剖系统分类对应的美术资源类别信息,将三维人体模型数据中与所述美术资源类别信息对应的美术资源数据分配到所述医学解剖分类数据组中,得到所述若干个分组数据。
  3. 根据权利要求2所述的人体模型数据处理方法,其中,所述将三维人体模型数据中与所述美术资源类别信息对应的美术资源数据分配到所述医学解剖分类数据组中之前,所述方法还包括:
    获取人体模型数据的运行平台的类型信息,根据所述运行平台的类型信息确定所述美术资源数据。
  4. 根据权利要求2或3所述的人体模型数据处理方法,其中,所述根据各个所述分组数据,确定所述分组数据中的重复资源,以及去除所述重复资源后的整理后分组数据包括:
    根据人体医学解剖分类信息中的公共信息,从所述若干个分组数据中提取与所述公共信息有关的数据并进行去重处理,得到所述重复资源;
    将所述与所述公共信息有关的数据从所述若干个分组数据中删除,得到所述整理后分组数据。
  5. 根据权利要求2所述的人体模型数据处理方法,其中,所述美术资源数据包括骨骼模型框架和附着丰富骨骼模型框架的贴图。
  6. 根据权利要求1所述的人体模型数据处理方法,其中,所述将所述重复资源打包为分包数据,将各个所述整理后分组数据分别打包为分包数据,包括:
    获取与所述重复资源和所述各个整理后分组数据对应的用户权限信息,在所述分包数据中添加所述用户权限信息。
  7. 根据权利要求1所述的人体模型数据处理方法,其中,所述存储全部所述分包数据,包括:
    将所述分包数据转码为二进制的分包数据;
    存储所述二进制的分包数据。
  8. 根据权利要求1所述的人体模型数据处理方法,其中,所述医学解剖分类信息包括以下至少一种:人体外形分类信息、人体器官分类信息或人体系统分类信息;美术资源类别信息包括二维资源信息和三维资源信息。
  9. 根据权利要求1所述的人体模型数据处理方法,其中,所述将所述重复资源打包为分包数据,将各所述整理后分组数据分别打包为分包数据,存储全部所述分包数据,包括:根据所述重复资源和各个所述整理后分组数据,确定分包目录表,所述分包目录表包括多条与所述分包数据一一对应的映射信息;
    存储所述分包目录表。
  10. 根据权利要求9所述的人体模型数据处理方法,其中,所述将所述重复资源打包为分包数据,将各所述整理后分组数据分别打包为分包数据,存储全部所述分包数据之后,所述方法还包括:
    响应于数据查询指令,显示根据整理后的所述人体系统分组数据确定的分包目录表,所述分包目录表包括多条与人体系统分包数据一一对应的映射信息,所述人体系统分包数据包括:运动系统分包数据、神经系统分包数据、内分泌系统分包数据、循环系统分包数据、呼吸系统分包数据、消化系统分包数据、泌尿系统分包数据和生殖系统分包数据;
    响应于针对所述分包目录表中的一条映射信息的查看请求,获取与所述 查看请求相对应的人体系统分包数据并显示。
  11. 一种人体模型数据展示方法,包括:
    响应于数据查询指令,获取与所述数据查询指令对应的人体模型的所述分包数据;所述分包数据采用权利要求1~10中任一项提供的人体模型数据处理方法确定;
    对所述分别数据进行解压缩处理并显示所述人体模型的分包数据。
  12. 根据权利要求11所述的人体模型数据展示方法,其中,所述响应于数据查询指令,获取与所述数据查询指令对应的人体模型的所述分包数据,包括:
    响应于数据查询指令,获取根据整理后的所述人体系统分组数据确定的分包目录表并显示所述分包目录表,所述分包目录表包括多条与人体系统分包数据一一对应的映射信息,所述人体系统分包数据包括:运动系统分包数据、神经系统分包数据、内分泌系统分包数据、循环系统分包数据、呼吸系统分包数据、消化系统分包数据、泌尿系统分包数据和生殖系统分包数据;
    响应于针对所述分包目录表中的一条映射信息的查看请求,获取与所述查看请求相对应的人体系统分包数据。
  13. 一种人体模型数据处理装置,包括:
    分组模块,用于获取三维人体模型数据,根据预定分类条件将三维人体模型数据分类为若干个分组数据,所述预定分类条件包括医学解剖分类信息和美术资源类别信息;
    整理模块,用于根据各个所述分组数据,确定所述分组数据中的重复资源,以及去除所述重复资源后的整理后分组数据;
    打包模块,用于将所述重复资源打包为分包数据,将各所述整理后分组数据分别打包为分包数据,存储全部所述分包数据。
  14. 一种电子设备,包括显示器,还包括:
    处理器;
    存储器,与所述处理器电连接;
    至少一个程序,被存储在所述存储器中并被配置为由所述处理器执行,所述至少一个程序被配置用于:实现如权利要求1~10中任一项所述的人体模 型数据处理方法,或如权利要求11或12所述的人体模型数据展示方法。
  15. 一种计算机可读存储介质,所述计算机可读存储介质存储有至少一条指令、至少一段程序、代码集或指令集,所述至少一条指令、所述至少一段程序、所述代码集或指令集由处理器加载并执行以实现如权利要求1~10中任一项所述的人体模型数据处理方法,或如权利要求11或12所述的人体模型数据展示方法。
PCT/CN2021/100335 2020-06-17 2021-06-16 人体模型数据处理方法、装置、电子设备及存储介质 WO2021254383A1 (zh)

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Publication number Priority date Publication date Assignee Title
CN111710051A (zh) * 2020-06-17 2020-09-25 京东方科技集团股份有限公司 人体模型数据处理方法、装置、电子设备及存储介质
CN112256428A (zh) * 2020-10-21 2021-01-22 赛尔网络有限公司 数据处理方法、装置、电子设备及存储介质
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107331272A (zh) * 2017-08-25 2017-11-07 宁波灵云科技信息服务有限公司 基于仿真技术的医学教学用人体模型及使用方法
CN109739548A (zh) * 2018-12-28 2019-05-10 Oppo广东移动通信有限公司 程序打包方法、程序打包装置及计算机可读存储介质
CN110222108A (zh) * 2019-05-28 2019-09-10 上海易点时空网络有限公司 用于数据格式化导出的数据处理方法及装置
WO2020103057A1 (zh) * 2018-11-21 2020-05-28 深圳市欢太科技有限公司 数据处理方法、装置、电子设备以及存储介质
CN111710051A (zh) * 2020-06-17 2020-09-25 京东方科技集团股份有限公司 人体模型数据处理方法、装置、电子设备及存储介质

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109670062A (zh) * 2018-12-12 2019-04-23 成都四方伟业软件股份有限公司 一种三维资源管理方法及装置

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107331272A (zh) * 2017-08-25 2017-11-07 宁波灵云科技信息服务有限公司 基于仿真技术的医学教学用人体模型及使用方法
WO2020103057A1 (zh) * 2018-11-21 2020-05-28 深圳市欢太科技有限公司 数据处理方法、装置、电子设备以及存储介质
CN109739548A (zh) * 2018-12-28 2019-05-10 Oppo广东移动通信有限公司 程序打包方法、程序打包装置及计算机可读存储介质
CN110222108A (zh) * 2019-05-28 2019-09-10 上海易点时空网络有限公司 用于数据格式化导出的数据处理方法及装置
CN111710051A (zh) * 2020-06-17 2020-09-25 京东方科技集团股份有限公司 人体模型数据处理方法、装置、电子设备及存储介质

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