CN111582680B - Visual evaluation method for user emotion based on VR game and storage medium - Google Patents
Visual evaluation method for user emotion based on VR game and storage medium Download PDFInfo
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- CN111582680B CN111582680B CN202010333487.0A CN202010333487A CN111582680B CN 111582680 B CN111582680 B CN 111582680B CN 202010333487 A CN202010333487 A CN 202010333487A CN 111582680 B CN111582680 B CN 111582680B
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Abstract
The invention relates to a visual evaluation method and a storage medium for user emotion based on VR games, comprising the following steps: step 101, determining influence factors of user emotion estimation; 102, establishing an evaluation index system for user emotion evaluation according to influence factors of the user emotion evaluation; step 103, calculating to obtain the index weight of the evaluation index system through an analytic hierarchy process; 104, obtaining an evaluation model of user emotion evaluation according to the index weight; step 105, obtaining the influence factors of the user, converting the influence factors of the user to obtain related scores of the influence factors, inputting the related scores into an evaluation model of the user emotion to obtain emotion evaluation scores of the user, and step 106, predicting emotion states of the user according to the emotion evaluation scores of the user. The invention can intelligently predict the emotion of the user, increases the VR game use experience of the user, and can provide a visual user evaluation standard.
Description
Technical Field
The invention relates to the field of artificial intelligence, in particular to a visual evaluation method and a storage medium for user emotion based on VR games.
Background
Currently, VR games are popular. In terms of user experience, the method still has some defects, the problem of lack of attention to the self condition of the user, and the method can not perform more information interaction with the user during use, can not enable the user to truly realize the experience of integrating into games, and also lacks a visual user evaluation standard.
Disclosure of Invention
The invention aims to solve one of the defects of the prior art and provides a user emotion visual evaluation method based on a VR game and a storage medium.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the invention provides a visual evaluation method of user emotion based on VR games, which comprises the following steps:
step 101, determining influence factors of user emotion evaluation, wherein the influence factors comprise sound decibels of a user when the user plays a VR game, the proportion of active words selected by the user to total words selected by the user and the number of times of average pulse of the user;
102, establishing an evaluation index system for user emotion evaluation according to influence factors of the user emotion evaluation;
step 103, calculating to obtain the index weight of the evaluation index system through an analytic hierarchy process;
104, obtaining an evaluation model of user emotion evaluation according to the index weight;
step 105, obtaining the influence factors of the user, converting the influence factors of the user to obtain related scores of the influence factors, and inputting the related scores into an evaluation model of the user emotion to obtain emotion evaluation scores of the user;
and 106, predicting the emotion state of the user according to the emotion evaluation score of the user, and displaying the emotion state.
Further, in the step 105, the step of converting the influence factor of the user to obtain the relevant score of the influence factor specifically includes the following steps:
acquiring sound decibel B of a user when the user plays a VR game, wherein the relevant score of the sound decibel B of the user is B/100;
acquiring the proportion L of the active vocabulary selected by the user to the total vocabulary to be selected, and setting the correlation score of the proportion L of the active vocabulary selected by the user to the total vocabulary to be selected;
and acquiring the number O of the average pulse of the user, wherein the relevant score of the number O of the average pulse of the user is O/80.
Further, the method for judging the proportion of the active vocabulary selected by the user to the total vocabulary comprises the following steps:
and constructing a VR game vocabulary database, wherein the VR game vocabulary database comprises all vocabularies which can be selected by a user in the VR game, the VR game vocabulary database is divided into two tables, namely a positive vocabulary and a non-positive vocabulary, the vocabularies selected by the user are searched, and if the positive vocabulary exists, the vocabularies are judged to be positive vocabularies.
Further, the index weights of the evaluation index system obtained in the step 103 specifically include the following:
determining the relative importance degree of each evaluation index, constructing a hierarchical structure model and a judgment matrix, and carrying out screening correction through consistency test to obtain the index weight of the evaluation index system.
Further, the method for determining the relative importance degree of each evaluation index is a method for establishing a judgment matrix by scoring by an established expert group, and calculating the index weight of the evaluation index system specifically comprises the following steps,
step 201, 5 experts are established, the 5 expert groups are numbered A1-A5 in sequence, the judging result of the expert groups on the relative importance degree of each evaluation index is obtained, and a judging matrix is established, wherein the judging matrix specifically comprises the following steps:
step 202, performing normalization processing on each column of elements of the judgment matrix, wherein general terms of the elements are as follows:
wherein a is ij Representing the elements of the ith row and the jth column of the judgment matrix;
step 203, performing row-by-row addition on the normalized judgment matrix of each column, and performing normalization processing to obtain a feature vector W of the judgment matrix, where the feature vector W is represented by the following formula:
step 204, obtaining the maximum feature root of the judgment matrix through the judgment matrix and the feature vector calculation
Therein (AmW) i The i-th element of the representation vector AmW, m is [1,5 ]]Am represents a correspondingly numbered judgment matrix;
step 205, performing consistency test on the judgment matrix to obtain index weights of all evaluation indexes, cr=ci/RI, where CI represents a consistency index,
RI represents a random uniformity index.
Further, the evaluation model for user emotion evaluation in step 104 specifically includes the following steps:
according to the calculated index weight, respectively setting the correlation score of sound decibels of a user when the user plays the VR game as Q1, and setting the corresponding index weight as Q1; the relevant score of the proportion of the active vocabulary selected by the user to the total vocabulary selected by the user is Q2, and the corresponding index weight is Q2; the relevant score of the number of the divided pulses of the user is Q3, the corresponding index weight is Q3,
the evaluation model m=q1+q1+q2+q2+q3 for the user affective evaluation.
Further, in the step 106, the emotion state of the user is predicted according to the emotion evaluation score of the user, and the emotion state is displayed, specifically including the following steps:
calculating to obtain a total section of the emotion evaluation score of the user, dividing the total section into 5 sections averagely, sequentially defining emotion evaluation results of the user falling into the 5 sections as very negative, slightly negative, common, slightly positive and very positive according to the sequence from small to large, and displaying corresponding emotion evaluation scores and emotion evaluation results.
The invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the steps of the user emotion visual evaluation method based on the VR game when being executed by a processor.
The beneficial effects of the invention are as follows:
according to the visual evaluation method for the emotion of the user based on the VR game, the VR game is used as a medium, three parameters including the sound decibel number of the user when the user plays the VR game in the process of experiencing the VR game, the proportion of active vocabularies selected by the user to the total vocabularies selected by the user and the number of times of average pulse of the user are collected, and an analytic hierarchy process model is built according to the three parameters, so that emotion of the user can be intelligently predicted, the use experience of the VR game of the user is increased, and a visual user evaluation standard can be provided.
Drawings
FIG. 1 is a flow chart of a method for visual evaluation of user emotion based on VR gaming.
Detailed Description
The conception, specific structure, and technical effects produced by the present invention will be clearly and completely described below with reference to the embodiments and the drawings to fully understand the objects, aspects, and effects of the present invention. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The same reference numbers will be used throughout the drawings to refer to the same or like parts.
With reference to fig. 1, the invention provides a visual evaluation method for user emotion based on a VR game, which comprises the following steps:
step 101, determining influence factors of user emotion evaluation, wherein the influence factors comprise sound decibels of a user when the user plays a VR game, the proportion of active words selected by the user to total words selected by the user and the number of times of average pulse of the user;
102, establishing an evaluation index system for user emotion evaluation according to influence factors of the user emotion evaluation;
step 103, calculating to obtain the index weight of the evaluation index system through an analytic hierarchy process;
104, obtaining an evaluation model of user emotion evaluation according to the index weight;
step 105, obtaining the influence factors of the user, converting the influence factors of the user to obtain related scores of the influence factors, and inputting the related scores into an evaluation model of the user emotion to obtain emotion evaluation scores of the user;
and 106, predicting the emotion state of the user according to the emotion evaluation score of the user, and displaying the emotion state.
As a preferred embodiment of the present invention, in the step 105, the converting the influencing factor of the user to obtain the relevant score of the influencing factor specifically includes the following steps:
acquiring sound decibel B of a user when the user plays a VR game, wherein the relevant score of the sound decibel B of the user is B/100;
acquiring the proportion L of the active vocabulary selected by the user to the total vocabulary to be selected, and setting the correlation score of the proportion L of the active vocabulary selected by the user to the total vocabulary to be selected;
and acquiring the number O of the average pulse of the user, wherein the relevant score of the number O of the average pulse of the user is O/80.
As a preferred embodiment of the present invention, the manner of judging the proportion of the active vocabulary selected by the user to the total vocabulary selected by the user specifically includes the following:
and constructing a VR game vocabulary database, wherein the VR game vocabulary database comprises all vocabularies which can be selected by a user in the VR game, the VR game vocabulary database is divided into two tables, namely a positive vocabulary and a non-positive vocabulary, the vocabularies selected by the user are searched, and if the positive vocabulary exists, the vocabularies are judged to be positive vocabularies.
As a preferred embodiment of the present invention, the index weights of the evaluation index system obtained in the step 103 include the following:
determining the relative importance degree of each evaluation index, constructing a hierarchical structure model and a judgment matrix, and carrying out screening correction through consistency test to obtain the index weight of the evaluation index system.
As a preferred embodiment of the present invention, the method for determining the relative importance of each evaluation index is a method for establishing a judgment matrix by scoring by establishing an expert group, calculating the index weight of the evaluation index system specifically includes,
step 201, 5 experts are established, the 5 expert groups are numbered A1-A5 in sequence, the judging result of the expert groups on the relative importance degree of each evaluation index is obtained, and a judging matrix is established, wherein the judging matrix specifically comprises the following steps:
step 202, performing normalization processing on each column of elements of the judgment matrix, wherein general terms of the elements are as follows:
wherein a is ij Representing the elements of the ith row and the jth column of the judgment matrix;
step 203, performing row-by-row addition on the normalized judgment matrix of each column, and performing normalization processing to obtain a feature vector W of the judgment matrix, where the feature vector W is represented by the following formula:
step 204, obtaining the maximum feature root of the judgment matrix through the judgment matrix and the feature vector calculation
Therein (AmW) i The i-th element of the representation vector AmW, m is [1,5 ]]Am represents a correspondingly numbered judgment matrix;
step 205, performing consistency test on the judgment matrix to obtain index weights of all evaluation indexes, cr=ci/RI, where CI represents a consistency index,
RI represents a random uniformity index.
Specifically, table 1 below shows the average random uniformity index RI
| n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| RI | 0 | 0.15 | 0.57 | 0.88 | 1.11 | 1.28 | 1.34 | 1.40 | 1.47 | 1.52 |
TABLE 1
When CR <0.10, the constructed judgment matrix is indicated to meet the consistency requirement, otherwise, the value of the judgment matrix is corrected.
The quantization value is determined by a scale method for the sound decibel number of the user when playing the VR game, the proportion of the active vocabulary selected by the user to the total vocabulary selected by the user, and the number of times of the average pulse of the user as shown in table 2 below,
| degree of importance among factors | Quantized value |
| Equally important | 1 |
| Slightly important | 3 |
| Is very important | 5 |
TABLE 2
As a preferred embodiment of the present invention, the evaluation model for user emotion evaluation in step 104 specifically includes the following:
according to the calculated index weight, respectively setting the correlation score of sound decibels of a user when the user plays the VR game as Q1, and setting the corresponding index weight as Q1; the relevant score of the proportion of the active vocabulary selected by the user to the total vocabulary selected by the user is Q2, and the corresponding index weight is Q2; the relevant score of the number of the divided pulses of the user is Q3, the corresponding index weight is Q3,
the evaluation model m=q1+q1+q2+q2+q3 for the user affective evaluation.
Specifically, in the present embodiment, each index weight is calculated as shown in the following table 3,
TABLE 3 Table 3
In a preferred embodiment of the present invention, the predicting the emotional state of the user according to the emotional evaluation score of the user in step 106 includes:
calculating to obtain a total section of the emotion evaluation score of the user, dividing the total section into 5 sections averagely, sequentially defining emotion evaluation results of the user falling into the 5 sections as very negative, slightly negative, common, slightly positive and very positive according to the sequence from small to large, and displaying corresponding emotion evaluation scores and emotion evaluation results.
The invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the steps of the user emotion visual evaluation method based on the VR game when being executed by a processor.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The integrated modules may be implemented in hardware or in software functional modules.
The integrated modules, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on this understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium may include content that is subject to appropriate increases and decreases as required by jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is not included as electrical carrier signals and telecommunication signals.
While the present invention has been described in considerable detail and with particularity with respect to several described embodiments, it is not intended to be limited to any such detail or embodiments or any particular embodiment, but is to be construed as providing broad interpretation of such claims by reference to the appended claims in view of the prior art so as to effectively encompass the intended scope of the invention. Furthermore, the foregoing description of the invention has been presented in its embodiments contemplated by the inventors for the purpose of providing a useful description, and for the purposes of providing a non-essential modification of the invention that may not be presently contemplated, may represent an equivalent modification of the invention.
The present invention is not limited to the above embodiments, but is merely preferred embodiments of the present invention, and the present invention should be construed as being limited to the above embodiments as long as the technical effects of the present invention are achieved by the same means. Various modifications and variations are possible in the technical solution and/or in the embodiments within the scope of the invention.
Claims (3)
1. The visual evaluation method of the user emotion based on the VR game is characterized by comprising the following steps of:
step 101, determining influence factors of user emotion evaluation, wherein the influence factors comprise sound decibels of a user when the user plays a VR game, the proportion of active words selected by the user to total words selected by the user and the number of times of average pulse of the user;
102, establishing an evaluation index system for user emotion evaluation according to influence factors of the user emotion evaluation;
step 103, calculating to obtain the index weight of the evaluation index system through an analytic hierarchy process;
104, obtaining an evaluation model of user emotion evaluation according to the index weight;
step 105, obtaining the influence factors of the user, converting the influence factors of the user to obtain related scores of the influence factors, and inputting the related scores into an evaluation model of the user emotion to obtain emotion evaluation scores of the user;
step 106, predicting the emotion state of the user according to the emotion evaluation score of the user and displaying the emotion state;
in the step 105, the relevant scores of the influence factors obtained by converting the influence factors of the user specifically include the following steps:
acquiring sound decibel B of a user when the user plays a VR game, wherein the relevant score of the sound decibel B of the user is B/100;
acquiring the proportion L of the active vocabulary selected by the user to the total vocabulary to be selected, and setting the correlation score of the proportion L of the active vocabulary selected by the user to the total vocabulary to be selected;
acquiring the number O of the average pulse of the user, wherein the relevant score of the number O of the average pulse of the user is O/80;
the index weights of the evaluation index system obtained in the step 103 specifically include the following:
determining the relative importance degree of each evaluation index, constructing a hierarchical structure model and a judgment matrix, and screening and correcting through consistency test to obtain the index weight of the evaluation index system;
the method for determining the relative importance degree of each evaluation index is a method for establishing a judgment matrix by scoring by an established expert group, and calculating the index weight of the evaluation index system specifically comprises the following steps,
step 201, establishing 5 expert groups, numbering 5 expert groups as A1-A5 in sequence, obtaining judgment results of the expert groups on the relative importance degree of each evaluation index, and establishing a judgment matrix, wherein the judgment matrix specifically comprises the following steps:
step 202, performing normalization processing on each column of elements of the judgment matrix, wherein general terms of the elements are as follows:
wherein a is ij Representing the elements of the ith row and the jth column of the judgment matrix;
step 203, performing row-by-row addition on the normalized judgment matrix of each column, and performing normalization processing to obtain a feature vector W of the judgment matrix, where the feature vector W is represented by the following formula:
step 204, obtaining the maximum feature root of the judgment matrix through the judgment matrix and the feature vector calculation
/>
Therein (AmW) i The i-th element of the representation vector AmW, m is [1,5 ]]Am represents a correspondingly numbered judgment matrix;
step 205, performing consistency test on the judgment matrix to obtain index weights of all evaluation indexes, cr=ci/RI, where CI represents a consistency index,
RI represents a random consistency index;
the evaluation model for user emotion evaluation in step 104 specifically includes the following steps:
according to the calculated index weight, respectively setting the correlation score of sound decibels of a user when the user plays the VR game as Q1, and setting the corresponding index weight as Q1; the relevant score of the proportion of the active vocabulary selected by the user to the total vocabulary selected by the user is Q2, and the corresponding index weight is Q2; the relevant score of the number of the divided pulses of the user is Q3, the corresponding index weight is Q3,
the evaluation model m=q1+q1+q2+q2+q3 for the user affective evaluation;
in the step 106, the emotion state of the user is predicted according to the emotion evaluation score of the user, and the emotion state is displayed, specifically including the following steps:
calculating to obtain a total section of the emotion evaluation score of the user, dividing the total section into 5 sections averagely, sequentially defining emotion evaluation results of the user falling into the 5 sections as very negative, slightly negative, common, slightly positive and very positive according to the sequence from small to large, and displaying corresponding emotion evaluation scores and emotion evaluation results.
2. The visual evaluation method of user emotion based on VR game according to claim 1, wherein the manner of judging the proportion of the positive vocabulary selected by the user to the total vocabulary selected by the user comprises the following steps:
and constructing a VR game vocabulary database, wherein the VR game vocabulary database comprises all vocabularies which can be selected by a user in the VR game, the VR game vocabulary database is divided into two tables, namely a positive vocabulary and a non-positive vocabulary, the vocabularies selected by the user are searched, and if the positive vocabulary exists, the vocabularies are judged to be positive vocabularies.
3. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any of claims 1-2.
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| CN104616232A (en) * | 2015-01-29 | 2015-05-13 | 河南卫豪实业有限公司 | Psychological assessment method based on mobile Internet technology |
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|---|---|---|---|---|
| CN101201980A (en) * | 2007-12-19 | 2008-06-18 | 北京交通大学 | Remote Chinese language teaching system based on voice affection identification |
| CN102169642A (en) * | 2011-04-06 | 2011-08-31 | 李一波 | Interactive virtual teacher system having intelligent error correction function |
| CN104616232A (en) * | 2015-01-29 | 2015-05-13 | 河南卫豪实业有限公司 | Psychological assessment method based on mobile Internet technology |
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