CN114068030B - Sand table splitting topic identification system, method and equipment based on visual analysis - Google Patents
Sand table splitting topic identification system, method and equipment based on visual analysis Download PDFInfo
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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Abstract
The invention belongs to the field of psychological sand table analysis, and particularly relates to a sand table splitting theme recognition system, method and device based on visual analysis, aiming at solving the problems of low accuracy and efficiency in the conventional manual recognition of a psychological sand table splitting theme. The system comprises: the data acquisition module is configured to acquire sand table work data; the separation degree determining module is configured to screen sand tools belonging to the segmentation class in the sand table works as first sand tools; counting the number of categories of the segmentation types of the first sand tool as the separation degree of the sand table works; the clustering module is configured to cluster the sand tools to obtain sand tool clusters; the isolation degree determining module is configured to obtain the isolation degree of the sand table work; and the classification subject identification module is configured to determine the splitting grade of the sand table works according to the separation grade and the isolation grade corresponding to the sand table works. The invention improves the accuracy and efficiency of recognizing the psychological sand table splitting theme.
Description
Technical Field
The invention belongs to the field of psychological sand table analysis, and particularly relates to a sand table splitting topic identification system, method and device based on visual analysis.
Background
The existing sand table theory mainly identifies psychological symptoms based on sand table subjects, and a sand table analyst analyzes subject categories appearing in the psychological sand table through the combination of theory and experience, so that the application of the initial sand table in clinic is achieved. In the identification process, the accurate finding of the theme appearing in the sand table becomes the key for the identification accuracy. The main identification indexes of the 'splitting' theme of the sand table are the separability and the insulativity among the sand tools in the sand table, and if the sand tools are separated by some sand tools of the segmentation class or the sand tools are isolated from each other in the spatial distribution, and the separated or isolated sand tools are not connected, the sand table work is called to meet the 'splitting' theme, and the scene 'splitting' degrees in the sand table works of different 'splitting' themes are different.
Existing sand table work split topic identification is mainly analyzed by sand table analysts. The sand table analyst has the following problems in the identification process: firstly, a sand table analyst generally utilizes experience to judge whether a sand table work meets a split theme, and the identification accuracy rate depends on the level of the sand table analyst; secondly, the manual identification is highly subjective, and the results given by different analysts have certain deviation. In order to more objectively identify the splitting theme of the sand table, the invention provides a system for automatically detecting and distinguishing the splitting degree in a visual image scene of the sand table, namely a sand table splitting theme identification system based on visual analysis.
Disclosure of Invention
In order to solve the above problems in the prior art, that is, to solve the problems of low accuracy and efficiency of the existing manual identification of the mental sand table splitting theme, a first aspect of the present invention provides a sand table splitting theme identification system based on visual analysis, the system comprising: the system comprises a data acquisition module, a separation degree determination module, a clustering module, an isolation degree determination module and a split topic identification module;
the data acquisition module is configured to acquire sand table work data corresponding to a sand table work made on a mental sand table by a visitor; the sand table work data comprise sand tool names, sand tool types, sand tool position information and sand tool distribution area information on the mental sand table;
the separation degree determining module is configured to screen sand tools belonging to a segmentation class in the sand table works as first sand tools based on the sand table work data; acquiring the segmentation type of each first sand tool according to the position information and the distribution region information of each first sand tool on the mental sand table and through the preset mapping relation between the distribution region and the segmentation type; counting the number of categories of the segmentation types of the first sand tool as the separation degree of the sand table works;
the clustering module is configured to cluster the sand tools by a preset neighborhood radius distance adaptive DBSCAN clustering method based on position information and distribution area information of the sand tools on the physical sand table in the sand table work data to obtain sand tool clusters;
the isolation degree determining module is configured to calculate the distance between each sand tool cluster and other sand tool clusters after clustering, and obtain the minimum distance in the distances as the shortest distance; if the shortest distance is smaller than a set distance threshold, taking the corresponding sand tool cluster as an isolated cluster; taking the ratio of the number of the isolated clusters to the total number of the sand tool clusters as the isolation degree of the sand table work;
the split subject identification module is configured to judge a threshold table based on a preset sand scene separation grade and an isolation grade, and match the obtained separation degree of the sand table works and the isolation degree of the sand table works to obtain the separation grade and the isolation grade corresponding to the sand table works; determining the splitting grade of the sand table works according to the corresponding separation grade and isolation grade of the sand table works;
the sand scene separation grade and isolation grade judgment threshold value table is a preset separation degree, a mapping relation between a preset separation grade threshold value and a preset separation grade, and a mapping relation between a preset isolation degree, a preset isolation grade threshold value and a preset isolation grade.
In some preferred embodiments, the preset neighborhood radius distance adaptive DBSCAN clustering method includes:
calculating the minimum circumscribed circle radius of the distribution area of each sand tool based on the distribution area information of each sand tool in the sand table work data;
calculating the space distance between every two sand tools;
judging whether the space distance between every two sand tools is smaller than the sum of the minimum circumscribed circle radius, and if so, gathering the two sand tools into one type;
and counting the number of the sand tools in each type after clustering, and if the number is larger than a set number threshold, keeping the current type.
In some preferred embodiments, the distance between the clustered sand tool clusters is calculated by:
calculating the mean value of the positions according to the position information of the sand tools in the sand tool clusters, and taking the mean value as the central coordinates of the sand tool clusters;
and calculating the distance between the center coordinates of the sand tool clusters as the distance between the clustered sand tool clusters.
In some preferred embodiments, the set distance threshold is a product of a diagonal distance of the mental sand table and 0.3.
In some preferred embodiments, the method for determining the split level of the sand table work according to the corresponding separation level and the isolation level of the sand table work comprises the following steps: and taking the maximum value of the separation grade and the isolation grade as the splitting grade of the sand table work.
In a second aspect of the present invention, a sand table splitting topic identification method based on visual analysis is provided, the method includes the following steps:
s100, collecting sand table work data corresponding to a sand table work made on a mental sand table by a visitor; the sand table work data comprise sand tool names, sand tool types, sand tool position information and sand tool distribution area information on the mental sand table;
step S200, screening sand tools belonging to segmentation class in the sand table works as first sand tools based on the sand table work data; acquiring the segmentation type of each first sand tool according to the position information and the distribution region information of each first sand tool on the mental sand table and through the preset mapping relation between the distribution region and the segmentation type; counting the number of categories of the segmentation types of the first sand tool as the separation degree of the sand table works;
step S300, based on position information and distribution area information of the sand tools on the physical sand table in the sand table work data, clustering the sand tools by a preset neighborhood radius distance adaptive DBSCAN clustering method to obtain sand tool clusters;
step S400, calculating the distance between each sand tool cluster and other sand tool clusters after clustering, and acquiring the minimum distance in the distances as the shortest distance; if the shortest distance is smaller than a set distance threshold, taking the corresponding sand tool cluster as an isolated cluster; taking the ratio of the number of the isolated clusters to the total number of the sand tool clusters as the isolation degree of the sand table work;
step S500, a threshold value table is judged based on preset sand scene separation levels and isolation levels, and the obtained separation degree of the sand table works and the isolation degree of the sand table works are matched to obtain the separation degree and the isolation degree corresponding to the sand table works; determining the splitting grade of the sand table works according to the corresponding separation grade and isolation grade of the sand table works;
the sand scene separation grade and isolation grade judgment threshold value table is a preset separation degree, a mapping relation between a preset separation grade threshold value and a preset separation grade, and a mapping relation between a preset isolation degree, a preset isolation grade threshold value and a preset isolation grade.
In a third aspect of the invention, an electronic device is proposed, at least one processor; and a memory communicatively coupled to at least one of the processors; wherein the memory stores instructions executable by the processor for execution by the processor to implement the visual analysis-based sand table splitting topic identification method described above.
In a fourth aspect of the present invention, a computer-readable storage medium is provided, where computer instructions are stored in the computer-readable storage medium, and the computer instructions are used for being executed by the computer to implement the above-mentioned sand table splitting topic identification method based on visual analysis.
The invention has the beneficial effects that:
the invention improves the accuracy and efficiency of recognizing the psychological sand table splitting theme.
Aiming at the popularization of market psychological sand tables and electronic psychological sand tables at the present stage, the invention provides a system for automatically identifying scene splitting degree in images, and the isolation degree and the separation degree of sand table works are obtained to further determine the splitting grade of the sand table works, so that the identification and judgment of the split theme of the sand table are realized, the workload of a sand table analyst is greatly reduced, the identification efficiency is increased, and the accuracy and the consistency of the split theme identification in the psychological sand table are improved.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings.
FIG. 1 is a schematic diagram of a framework of a sand table splitting topic identification system based on visual analysis according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a visual analysis-based sand table splitting topic identification system according to an embodiment of the invention;
FIG. 3 is a schematic diagram of a sand table splitting topic identification system based on visual analysis to identify the splitting level of a sand table work according to an embodiment of the invention;
FIG. 4 is a flow chart of a sand table splitting topic identification method based on visual analysis according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a computer system suitable for implementing an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The sand table splitting topic identification system based on visual analysis of the invention, as shown in fig. 1, comprises: the system comprises: the system comprises a data acquisition module 100, a separation degree determination module 200, a clustering module 300, an isolation degree determination module 400 and a split topic identification module 500;
the data acquisition module 100 is configured to acquire sand table work data corresponding to a sand table work made by a visitor on a mental sand table; the sand table work data comprise sand tool names, sand tool types, sand tool position information and sand tool distribution area information on the mental sand table;
the separation degree determining module 200 is configured to screen sand tools belonging to a segmentation class in the sand table works as first sand tools based on the sand table work data; acquiring the segmentation type of each first sand tool according to the position information and the distribution region information of each first sand tool on the mental sand table and through the preset mapping relation between the distribution region and the segmentation type; counting the number of categories of the segmentation types of the first sand tool as the separation degree of the sand table works;
the clustering module 300 is configured to cluster the sanders by a preset neighborhood radius distance adaptive DBSCAN clustering method based on the position information and the distribution area information of the sanders on the physical sand table in the data of the sandtable works to obtain a sandware cluster;
the isolation degree determining module 400 is configured to calculate distances between each sand tool cluster and other sand tool clusters after clustering, and obtain the smallest one of the distances as the shortest distance; if the shortest distance is smaller than a set distance threshold, taking the corresponding sand tool cluster as an isolated cluster; taking the ratio of the number of the isolated clusters to the total number of the sand tool clusters as the isolation degree of the sand table work;
the split subject identification module 500 is configured to judge a threshold table based on a preset sand scene separation level and an isolation level, and match the obtained separation degree of the sand table works and the isolation degree of the sand table works to obtain the separation level and the isolation level corresponding to the sand table works; determining the splitting grade of the sand table works according to the corresponding separation grade and isolation grade of the sand table works;
the sand scene separation grade and isolation grade judgment threshold value table is a preset separation degree, a mapping relation between a preset separation grade threshold value and a preset separation grade, and a mapping relation between a preset isolation degree, a preset isolation grade threshold value and a preset isolation grade.
In order to more clearly describe the sand table splitting topic identification system based on visual analysis, the following describes the modules in various embodiments of the system in detail with reference to the attached drawings.
In psychology, division means "a state in which the individual elements constituting the whole are separated or isolated from each other". Therefore, the psychological sand table splitting theme can be particularly expressed in two types of scenes, one type is a separating scene, and mainly means that the splitting sand tools (such as rivers, enclosing walls and the like) contained in the sand table spatially separate other common sand tools; another class is the solitary scene, which primarily refers to the presence of a single sand in a sand table or between clusters of multiple sands that are spatially isolated from each other.
Corresponding to the two types of splitting scenarios described above, the determination of the splitting topic of the present invention is also discussed based thereon. As shown in fig. 2, first, for a sand table work which a visitor has put on, the category information, the position information and the distribution area information of the sand tools appearing therein can be obtained. Then, based on these pieces of information, the above-described two types of scenes are judged. And finally, determining the final splitting grade of the sand table by integrating the separation degree and the isolation degree information of the sand table. Based on the above, the invention provides a sand table splitting topic identification system based on visual analysis. The method comprises the following specific steps:
the sand table splitting topic identification system based on visual analysis of the invention, as shown in fig. 1, comprises a data acquisition module 100, a separation degree determination module 200, a clustering module 300, an isolation degree determination module 400 and a splitting topic identification module 500;
the data acquisition module 100 is configured to acquire sand table work data corresponding to a sand table work made by a visitor on a mental sand table; the sand table work data comprise sand tool names, sand tool types, sand tool position information and sand tool distribution area information on the mental sand table;
in this embodiment, the sand table work data corresponding to the sand table work made by the visitor on the mental sand table, that is, the sand file in fig. 3, is collected. Or the image of the sand table work (picture) made on the mental sand table by the visitor can be collected by the camera device, and the sand table work image is subjected to image recognition (the image recognition method is the prior art, and is not described here any more), so that the sand table work data is obtained.
The separation degree determining module 200 is configured to screen sand tools belonging to a segmentation class in the sand table works as first sand tools based on the sand table work data; acquiring the segmentation type of each first sand tool according to the position information and the distribution region information of each first sand tool on the mental sand table and through the preset mapping relation between the distribution region and the segmentation type; counting the number of categories of the segmentation types of the first sand tool as the separation degree of the sand table works;
in this embodiment, first, according to the classification information of the sandstones in the input sand table work, the sand tools of the segmentation class in the work can be screened out (or called segmentation class sand tools, which are set types of sand tools including rivers and walls; in other embodiments, the sand tools can be selected according to the actual situation). Then, based on the position information and the distribution area information of the divided sand-like tools, the separation degree of the sand table is obtained, as in the separation degree judgment step in fig. 3.
In order to better measure the index of the separation degree, the distribution area of the segmentation sand tools in the image should not be taken as a measure, and the influence caused by the 'segmentation type' of the sand tools should be taken into consideration. The "division type" herein may be defined according to the distribution characteristics of the division-type sandtools in the entire picture, for example, if the distribution of one division-type sandtool covers the upper and right ends of the entire sand table, the division type of this division-type sandtool is "division of the upper right and lower left areas of the sand table", and it is known from the discussion that the division types include "division of the upper right and lower left areas of the sand table", "division of the upper left and lower right areas of the sand table", "division of the left and right areas of the sand table", and "division of the upper and lower areas of the sand table", in which the upper, lower, left, and right are orientation divisions equally divided according to the length and width of the image of the sandtool work.
And counting the total number of the segmentation types of all the segmentation sand tools in the sand table, and taking the total number as an index for measuring the separation degree.
The clustering module 300 is configured to cluster the sanders by a preset neighborhood radius distance adaptive DBSCAN clustering method based on the position information and the distribution area information of the sanders on the physical sand table in the data of the sandtable works to obtain a sandware cluster;
in the present embodiment, first, clustering processing is performed on the sandtools based on the positional information and the distribution area information of the sandtools. The invention provides a DBSCAN clustering method with adaptive neighborhood radius distance. For the DBSCAN clustering method, the minimum neighborhood distance is preset
And minimum cluster sample point number
Based on these two hyper-parameters (as long as the distance between two points is less than
Considering the two points as reachable in density, i.e. considering the two points belong to the same class, after traversing all the points, if the number of sample points in one class is larger than that of sample points in one class
The sample point is regarded as a cluster to be finally obtained as a sand tool cluster, and if the sample point is less than or equal to the sand tool cluster
Then the sand distribution is considered to be dispersed, no cluster is formed, and no analysis is subsequently performed thereon), which can adapt to the cluster number and can find clusters of any shape. Due to the different sizes of different sand tools in the sand table, the over-parameters can be caused
And is also changed accordingly.
The invention designs a pair of over-parameters by combining the distribution range information of the sand tools
And (4) self-adaptive clustering algorithm. Firstly, according to the distribution area information of the sand tool, calculating the minimum circumscribed circle radius of the distribution area surrounding the sand tool; and then when the density between the two sand tools can be judged, if the space distance between the two sand tools is smaller than the sum of the minimum circumscribed circle radius of the two sand tools, the two sand tools are considered to be density-reachable, and the two sand tools are gathered into the same type. Based on the method, only the setting is needed
The super-parameter can realize clustering operation on sand tools with different sizes. The method specifically comprises the following steps:
counting the number of the sand tools in each type after clustering, if the number is larger than a set number threshold value
If not, the sand tools are distributed dispersedly, and do not form a cluster, namely, the current class is not reserved.
The isolation degree determining module 400 is configured to calculate distances between each sand tool cluster and other sand tool clusters after clustering, and obtain the smallest one of the distances as the shortest distance; if the shortest distance is smaller than a set distance threshold, taking the corresponding sand tool cluster as an isolated cluster; taking the ratio of the number of the isolated clusters to the total number of the sand tool clusters as the isolation degree of the sand table work;
in the embodiment, the isolation degree of each sand tool cluster is determined by judging the distance between each sand tool cluster, as shown in the step of judging the isolation degree in fig. 3. The method comprises the following specific steps:
obtaining the sand tools by calculating the position average value according to the position information of each sand tool in each sand tool clusterA center coordinate of the cluster; regarding the central coordinates of the sand tool clusters as the overall position coordinates of the sand tool clusters, respectively calculating the distance between the central coordinates of each sand tool cluster and the central coordinates of the other sand tool clusters, and recording the shortest distance value; if the shortest distance value is greater than the set distance threshold (i.e. the shortest distance value is greater than the set distance threshold)
) Then the sand tool cluster is considered as an isolated cluster; after the isolated state of each sand tool cluster is determined, the ratio of the number of the isolated clusters to the total number of the sand tool clusters is calculated and used as an index for subsequently determining the isolated level of the sand table.
The split subject identification module 500 is configured to judge a threshold table based on a preset sand scene separation level and an isolation level, and match the obtained separation degree of the sand table works and the isolation degree of the sand table works to obtain the separation level and the isolation level corresponding to the sand table works; determining the splitting grade of the sand table works according to the corresponding separation grade and isolation grade of the sand table works;
the sand scene separation grade and isolation grade judgment threshold value table is a preset separation degree, a mapping relation between a preset separation grade threshold value and a preset separation grade, and a mapping relation between a preset isolation degree, a preset isolation grade threshold value and a preset isolation grade.
In this embodiment, after the total number (i.e., the number of categories) of the partition type sand tools and the ratio of the number of the isolated clusters to the total number of the sand tools are obtained, the separation level and the isolated level of the sand table work are obtained by combining with the threshold set according to the actual situation, and the maximum value of the separation level and the isolated level is taken as the final division level of the sand table work.
The separation grade determined by the number of the segmentation types is obtained by combining the actual cases, and the specific threshold information of the isolation grade is determined by the ratio of the number of the isolated clusters to the total number of the sand tool clusters, as shown in table 1:
TABLE 1
The table 1 is a threshold value table determined based on a preset sand scene separation level and an isolation level, and the threshold value table determined based on the preset sand scene separation level and the isolation level is a preset separation degree, a mapping relation between a preset separation level threshold value and a preset separation level, and a mapping relation between a preset isolation degree, a preset isolation level threshold value and a preset isolation level. The specific mapping relationship is shown in table 1.
In addition, in order to verify the effectiveness of the invention, a verification test is carried out on an AI heart world game platform (a 3D sand table game developed by an intelligent system of a Chinese academy of automation and an engineering technology research center). Tests show that the sand table splitting theme recognition system based on the visual analysis well realizes splitting theme judgment and can be used for realizing the autonomous judgment of a machine on the splitting theme of a psychological sand table.
It should be noted that, the sand table splitting topic identification system based on visual analysis provided in the foregoing embodiment is only illustrated by the division of the above functional modules, and in practical applications, the above functions may be allocated to different functional modules according to needs, that is, the modules or steps in the embodiment of the present invention are further decomposed or combined, for example, the modules in the foregoing embodiment may be combined into one module, or may be further split into multiple sub-modules, so as to complete all or part of the above described functions. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not to be construed as unduly limiting the present invention.
A sand table splitting topic identification method based on visual analysis according to a second embodiment of the present invention, as shown in fig. 4, includes the following steps:
s100, collecting sand table work data corresponding to a sand table work made on a mental sand table by a visitor; the sand table work data comprise sand tool names, sand tool types, sand tool position information and sand tool distribution area information on the mental sand table;
step S200, screening sand tools belonging to segmentation class in the sand table works as first sand tools based on the sand table work data; acquiring the segmentation type of each first sand tool according to the position information and the distribution region information of each first sand tool on the mental sand table and through the preset mapping relation between the distribution region and the segmentation type; counting the number of categories of the segmentation types of the first sand tool as the separation degree of the sand table works;
step S300, based on position information and distribution area information of the sand tools on the physical sand table in the sand table work data, clustering the sand tools by a preset neighborhood radius distance adaptive DBSCAN clustering method to obtain sand tool clusters;
step S400, calculating the distance between each sand tool cluster and other sand tool clusters after clustering, and acquiring the minimum distance in the distances as the shortest distance; if the shortest distance is smaller than a set distance threshold, taking the corresponding sand tool cluster as an isolated cluster; taking the ratio of the number of the isolated clusters to the total number of the sand tool clusters as the isolation degree of the sand table work;
step S500, a threshold value table is judged based on preset sand scene separation levels and isolation levels, and the obtained separation degree of the sand table works and the isolation degree of the sand table works are matched to obtain the separation degree and the isolation degree corresponding to the sand table works; determining the splitting grade of the sand table works according to the corresponding separation grade and isolation grade of the sand table works;
the sand scene separation grade and isolation grade judgment threshold value table is a preset separation degree, a mapping relation between a preset separation grade threshold value and a preset separation grade, and a mapping relation between a preset isolation degree, a preset isolation grade threshold value and a preset isolation grade.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process and related description of the method described above may refer to the corresponding process in the foregoing system embodiment, and are not described herein again.
The sand table splitting topic identification device based on visual analysis comprises image acquisition equipment and central processing equipment;
the image acquisition equipment comprises a video camera and a camera and is used for acquiring sand table work images corresponding to sand table works made on a mental sand table by visitors;
the central processing equipment comprises a GPU (graphics processing unit) which is configured to identify the sand table work image and acquire sand table work data corresponding to the sand table work; the sand table work data comprise sand tool names, sand tool types, sand tool position information and sand tool distribution area information on the mental sand table;
screening sand tools belonging to the segmentation class in the sand table works as first sand tools based on the sand table work data; acquiring the segmentation type of each first sand tool according to the position information and the distribution region information of each first sand tool on the mental sand table and through the preset mapping relation between the distribution region and the segmentation type; counting the number of categories of the segmentation types of the first sand tool as the separation degree of the sand table works;
clustering the sand tools by a preset neighborhood radius distance adaptive DBSCAN clustering method based on the position information and the distribution area information of the sand tools on the physical sand table in the sand table work data to obtain sand tool clusters;
calculating the distance between each sand tool cluster and other sand tool clusters after clustering, and acquiring the minimum distance as the shortest distance; if the shortest distance is smaller than a set distance threshold, taking the corresponding sand tool cluster as an isolated cluster; taking the ratio of the number of the isolated clusters to the total number of the sand tool clusters as the isolation degree of the sand table work;
judging a threshold table based on a preset sand scene separation grade and an isolation grade, and matching the obtained separation degree of the sand table works and the isolation degree of the sand table works to obtain the separation grade and the isolation grade corresponding to the sand table works; and determining the splitting grade of the sand table works according to the separation grade and the isolation grade corresponding to the sand table works.
An electronic device according to a fourth embodiment of the present invention includes at least one processor; and a memory communicatively coupled to at least one of the processors; wherein the memory stores instructions executable by the processor for execution by the processor to implement the visual analysis-based sand table splitting topic identification method described above.
A computer-readable storage medium of a fifth embodiment of the present invention stores computer instructions for being executed by the computer to implement the sand table splitting topic identification method based on visual analysis.
It can be clearly understood by those skilled in the art that, for convenience and brevity, the specific working processes and related descriptions of the sand table splitting topic identification apparatus based on visual analysis, the electronic device, and the computer-readable storage medium described above may refer to the corresponding processes in the foregoing method examples, and are not described herein again.
Referring now to FIG. 5, there is illustrated a block diagram of a computer system suitable for use as a server in implementing embodiments of the method, system, and apparatus of the present application. The server shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 5, the computer system includes a Central Processing Unit (CPU) 501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM503, various programs and data necessary for system operation are also stored. The CPU501, ROM 502, and RAM503 are connected to each other via a bus 504. An Input/Output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output section 507 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage portion 508 including a hard disk and the like; and a communication section 509 including a Network interface card such as a LAN (Local Area Network) card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. More specific examples of a computer-readable storage medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, 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), a compact disc read-only memory (CD-ROM), Optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The terms "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing or implying a particular order or sequence.
The terms "comprises," "comprising," or any other similar term are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
Claims (8)
1. A visual analysis-based sand table splitting topic identification system, the system comprising: the system comprises a data acquisition module, a separation degree determination module, a clustering module, an isolation degree determination module and a split topic identification module;
the data acquisition module is configured to acquire sand table work data corresponding to a sand table work made on a mental sand table by a visitor; the sand table work data comprise sand tool names, sand tool types, sand tool position information and sand tool distribution area information on the mental sand table;
the separation degree determining module is configured to screen sand tools belonging to a segmentation class in the sand table works as first sand tools based on the sand table work data; acquiring the segmentation type of each first sand tool according to the position information and the distribution region information of each first sand tool on the mental sand table and through the preset mapping relation between the distribution region and the segmentation type; counting the number of categories of the segmentation types of the first sand tool as the separation degree of the sand table works;
the clustering module is configured to cluster the sand tools by a preset neighborhood radius distance adaptive DBSCAN clustering method based on position information and distribution area information of the sand tools on the physical sand table in the sand table work data to obtain sand tool clusters;
the isolation degree determining module is configured to calculate the distance between each sand tool cluster and other sand tool clusters after clustering, and obtain the minimum distance in the distances as the shortest distance; if the shortest distance is greater than a set distance threshold, taking the corresponding sand tool cluster as an isolated cluster; taking the ratio of the number of the isolated clusters to the total number of the sand tool clusters as the isolation degree of the sand table work;
the split subject identification module is configured to judge a threshold table based on a preset sand scene separation grade and an isolation grade, and match the obtained separation degree of the sand table works and the isolation degree of the sand table works to obtain the separation grade and the isolation grade corresponding to the sand table works; determining the splitting grade of the sand table works according to the corresponding separation grade and isolation grade of the sand table works;
the sand scene separation grade and isolation grade judgment threshold value table is a preset separation degree, a mapping relation between a preset separation grade threshold value and a preset separation grade, and a mapping relation between a preset isolation degree, a preset isolation grade threshold value and a preset isolation grade.
2. The visual analysis-based sand table splitting topic identification system according to claim 1, wherein the preset neighborhood radius distance adaptive DBSCAN clustering method is as follows:
calculating the minimum circumscribed circle radius of the distribution area of each sand tool based on the distribution area information of each sand tool in the sand table work data;
calculating the space distance between every two sand tools;
judging whether the space distance between every two sand tools is smaller than the sum of the minimum circumscribed circle radius, and if so, gathering the two sand tools into one type;
and counting the number of the sand tools in each type after clustering, and if the number is larger than a set number threshold, keeping the current type.
3. The visual analysis-based sand table splitting topic identification system of claim 1, wherein the distance between sand tool clusters after clustering is calculated by:
calculating the mean value of the positions according to the position information of the sand tools in the sand tool clusters, and taking the mean value as the central coordinates of the sand tool clusters;
and calculating the distance between the center coordinates of the sand tool clusters as the distance between the clustered sand tool clusters.
4. The visual analysis-based sand table splitting topic identification system of claim 1, wherein the set distance threshold is a product of a diagonal distance of a psychological sand table and 0.3.
5. The sand table splitting topic identification system based on visual analysis as claimed in claim 1 wherein the splitting level of the sand table work is determined according to the corresponding separation level and isolation level of the sand table work, and the method is as follows: and taking the maximum value of the separation grade and the isolation grade as the splitting grade of the sand table work.
6. A sand table splitting topic identification method based on visual analysis is characterized by comprising the following steps:
s100, collecting sand table work data corresponding to a sand table work made on a mental sand table by a visitor; the sand table work data comprise sand tool names, sand tool types, sand tool position information and sand tool distribution area information on the mental sand table;
step S200, screening sand tools belonging to segmentation class in the sand table works as first sand tools based on the sand table work data; acquiring the segmentation type of each first sand tool according to the position information and the distribution region information of each first sand tool on the mental sand table and through the preset mapping relation between the distribution region and the segmentation type; counting the number of categories of the segmentation types of the first sand tool as the separation degree of the sand table works;
step S300, based on position information and distribution area information of the sand tools on the physical sand table in the sand table work data, clustering the sand tools by a preset neighborhood radius distance adaptive DBSCAN clustering method to obtain sand tool clusters;
step S400, calculating the distance between each sand tool cluster and other sand tool clusters after clustering, and acquiring the minimum distance in the distances as the shortest distance; if the shortest distance is greater than a set distance threshold, taking the corresponding sand tool cluster as an isolated cluster; taking the ratio of the number of the isolated clusters to the total number of the sand tool clusters as the isolation degree of the sand table work;
step S500, a threshold value table is judged based on preset sand scene separation levels and isolation levels, and the obtained separation degree of the sand table works and the isolation degree of the sand table works are matched to obtain the separation degree and the isolation degree corresponding to the sand table works; determining the splitting grade of the sand table works according to the corresponding separation grade and isolation grade of the sand table works;
the sand scene separation grade and isolation grade judgment threshold value table is a preset separation degree, a mapping relation between a preset separation grade threshold value and a preset separation grade, and a mapping relation between a preset isolation degree, a preset isolation grade threshold value and a preset isolation grade.
7. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to at least one of the processors; wherein the content of the first and second substances,
the memory stores instructions executable by the processor for execution by the processor to implement the visual analytics based sand table splitting topic identification method of claim 6.
8. A computer-readable storage medium storing computer instructions for execution by the computer to implement the visual analysis-based sand table splitting topic identification method of claim 6.
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