CN110415015A - Product degree of recognition analysis method, device, terminal and computer readable storage medium - Google Patents
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Abstract
The present invention relates to artificial intelligence fields, disclose a kind of product degree of recognition analysis method, comprising: obtain the video image in the product introduction period；Identification is carried out to video image and obtains the corresponding micro- expression type of the micro- expression of face and the corresponding instantaneous confidence level of micro- expression type in video image；Corresponding related coefficient is obtained according to micro- expression type；Instantaneous confidence level and related coefficient are inserted into investment willingness degree formula, obtain product moment degree of recognition；Client is obtained to the degree of recognition of product according to the product moment degree of recognition in the product introduction period.The present invention also provides a kind of product degree of recognition analytical equipment, terminal and computer readable storage mediums.Technical solution proposed by the present invention is based on micro- Expression Recognition and identifies to the micro- expression of face in video image, to obtain client to the degree of recognition of product, client can be obtained to the degree of recognition of product by being identified to video image, can be improved the analysis efficiency to the degree of recognition of product.
Description
Technical field
The present invention relates to field of artificial intelligence more particularly to a kind of product degree of recognition analysis method, device, terminal and
Computer readable storage medium.
Background technique
Currently, the business personnel of financial company at this stage after having introduced financial product to client, needs to know finance
Whether the recommendation of product succeeds, that is, needs to know whether client approves the financial product of introduction.Existing acquisition client is to production
The mode whether product are approved is to carry out artificial pay a return visit to client to investigate, and still, the mode manually investigated needs to expend a large amount of people
Power cost, so that product degree of recognition analysis efficiency is low.
Therefore, it is a kind of urgent problem to be solved that existing product degree of recognition analysis efficiency is low.
Summary of the invention
The main purpose of the present invention is to provide a kind of product degree of recognition analysis method, device, terminals and computer-readable
Storage medium, it is intended to solve the low technical problem of existing product degree of recognition analysis efficiency.
To achieve the above object, the present invention provides a kind of product degree of recognition analysis method, product degree of recognition analysis side
Method includes:
Obtain the video image in the product introduction period；
To the video image carry out identification obtain in the video image the corresponding micro- expression type of the micro- expression of face with
And the corresponding instantaneous confidence level of micro- expression type；
Corresponding related coefficient is obtained according to micro- expression type；
The instantaneous confidence level and the related coefficient are inserted into investment willingness degree formula, obtain product moment degree of recognition；
Client is obtained to the degree of recognition of product according to the product moment degree of recognition in the product introduction period.
Preferably, the investment willingness degree formula isWherein, piRefer to the corresponding correlation of micro- expression type i
Coefficient, qiRefer to the corresponding moment instantaneous confidence level of micro- expression type i, R refers to product moment degree of recognition.
Preferably, the product moment degree of recognition according in the product introduction period obtains client to the approval journey of product
The step of spending include:
Product moment degree of recognition of the single client to product in the acquisition product introduction period；
Single client in the product introduction period is drawn out according to the product moment degree of recognition to walk micro- expression of product
Gesture figure；
Single client is obtained to the degree of recognition grade of product according to micro- expression trend graph.
Preferably, described that single client is drawn out in the product introduction period to product according to the product moment degree of recognition
Micro- expression trend graph the step of after, further includes:
Art is talked about in the sale obtained in the product introduction period；
Micro- expression tendency of product under each sale words art is obtained according to micro- expression trend graph of product；
Crucial words art is obtained according to micro- expression tendency of product under each sale words art, and the crucial words art is added to
Intelligence words art library.
Preferably, described the step of degree of recognition grade of the single client to product is obtained according to micro- expression trend graph
Later, further includes:
Degree of recognition grade of all clients to identical product in the acquisition product introduction period；
Count client's number of different product degree of recognition grades；
Market is obtained to the degree of recognition of identical product according to client's number.
Preferably, described the step of degree of recognition grade of the single client to product is obtained according to micro- expression trend graph
Later, further includes:
Degree of recognition grade of the single client to different product in the acquisition product introduction period；
Single client is drawn out to the preference point of different product according to degree of recognition grade of the single client to different product
Butut；
The product preference of client is obtained according to the preference distribution figure.
Preferably, described identify that the micro- expression of face is corresponding micro- in the acquisition video image to the video image
The step of expression type and micro- expression type corresponding instantaneous confidence level includes:
Identification is carried out to the video image and obtains the corresponding micro- expressive features of the micro- expression of face in the video image；
Corresponding micro- expression type is obtained according to the micro- expressive features and micro- expression type is corresponding instantaneously sets
Reliability.
In addition, the present invention also provides a kind of product degree of recognition analytical equipment, the product degree of recognition analytical equipment includes:
First obtains module, and the first acquisition module is used to obtain the video image in the product introduction period；
Identification module, the identification module are used to carry out the video image identification to obtain face in the video image
Micro- corresponding micro- expression type of expression and the corresponding instantaneous confidence level of micro- expression type；
Second obtains module, and described second, which obtains module, is used to obtain corresponding phase relation according to micro- expression type
Number；
Computing module, the computing module are used to the instantaneous confidence level and the related coefficient inserting investment willingness degree
Formula obtains product moment degree of recognition；
Third obtains module, and the third obtains module and is used for according to the product moment degree of recognition in the product introduction period
Client is obtained to the degree of recognition of product.
The present invention also provides a kind of terminal, including processor, memory and be stored on the memory can be by institute
State the product degree of recognition analysis program of processor execution, wherein the product degree of recognition analysis program is executed by the processor
When, the step of realizing product degree of recognition analysis method as described above.
The present invention also provides a kind of computer readable storage medium, product is stored on the computer readable storage medium
Degree of recognition analyzes program, wherein when the product degree of recognition analysis program is executed by processor, realizes that product as described above is recognized
The step of analysis method can be spent.
In technical solution of the present invention, the video image in the product introduction period is obtained；Identification is carried out to video image to obtain
Take the corresponding micro- expression type of the micro- expression of face and the corresponding instantaneous confidence level of micro- expression type in video image；According to micro- table
Feelings type obtains corresponding related coefficient；Instantaneous confidence level and related coefficient are inserted into investment willingness degree formula, obtain product wink
Between degree of recognition；Client is obtained to the degree of recognition of product according to the product moment degree of recognition in the product introduction period.The present invention
The technical solution of proposition is based on micro- Expression Recognition and identifies to the micro- expression of face in video image, will be corresponding with micro- expression type
Instantaneous confidence level and related coefficient insert investment willingness degree formula, obtain product moment degree of recognition, and recognize according to product moment
It can spend and obtain client to the degree of recognition of product, more preferably can more accurately instruct the financing marketing of financial business personnel's reasonable disposition
Activity.The present invention can obtain client to the degree of recognition of product by being identified to video image, can be improved to product
The analysis efficiency of degree of recognition.
Detailed description of the invention
Fig. 1 is the hardware structural diagram of terminal involved in the embodiment of the present invention；
Fig. 2 is the flow diagram of product of the present invention degree of recognition analysis method first embodiment；
Fig. 3 is to carry out identification to the video image in the embodiment of the present invention to obtain the micro- expression of face in the video image
The process refinement schematic diagram of the step of corresponding micro- expression type and micro- expression type corresponding instantaneous confidence level；
Fig. 4 is to obtain client to product according to the product moment degree of recognition in the product introduction period in the embodiment of the present invention
The degree of recognition the step of process refinement schematic diagram；
Fig. 5 is the flow diagram of product of the present invention degree of recognition analysis method second embodiment；
Fig. 6 is the flow diagram of product of the present invention degree of recognition analysis method 3rd embodiment；
Fig. 7 is the flow diagram of product of the present invention degree of recognition analysis method fourth embodiment；
Fig. 8 is the module diagram of product of the present invention degree of recognition analytical equipment.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
The present embodiments relate to product degree of recognition analysis method be mainly used in terminal, which can be PC, just
Take the equipment that computer, mobile terminal etc. have display and processing function.
Referring to Fig.1, Fig. 1 is terminal structure schematic diagram involved in the embodiment of the present invention.In the embodiment of the present invention, eventually
End may include processor 1001 (such as CPU), communication bus 1002, user interface 1003, network interface 1004, memory
1005.Wherein, communication bus 1002 is for realizing the connection communication between these components；User interface 1003 may include display
Shield (Display), input unit such as keyboard (Keyboard)；Network interface 1004 optionally may include that the wired of standard connects
Mouth, wireless interface (such as WI-FI interface)；Memory 1005 can be high speed RAM memory, be also possible to stable memory
(non-volatile memory), such as magnetic disk storage, memory 1005 optionally can also be independently of aforementioned processor
1001 storage device.
It will be understood by those skilled in the art that hardware configuration shown in Fig. 1 does not constitute the restriction to equipment, can wrap
It includes than illustrating more or fewer components, perhaps combines certain components or different component layouts.
With continued reference to Fig. 1, the memory 1005 in Fig. 1 as a kind of computer readable storage medium may include operation system
System, network communication module and product degree of recognition analyze program.
In Fig. 1, network communication module is mainly used for connecting server, carries out data communication with server；And processor
1001 can call the product degree of recognition stored in memory 1005 to analyze program, and execute the step of product degree of recognition analysis method
Suddenly.
Based on the hardware configuration of above-mentioned terminal, each embodiment of product of the present invention degree of recognition analysis method is proposed.
The present invention provides a kind of product degree of recognition analysis method.
Referring to Fig. 2, in the first embodiment of the invention, product degree of recognition analysis method the following steps are included:
Step S100 obtains the video image in the product introduction period；
It specifically, can be when the business personnel of financial industry introduces financial product to client, to the facial expression of client
It records a video, video image after business personnel introduces, in the available product introduction period.It is equipped in the terminal
The micro- expression model of product degree of recognition, by the micro- expression model of video image input product degree of recognition in the product introduction period,
Terminal will acquire the video image in the product introduction period, to divide the video image in the product introduction period
Analysis.
Step S200 carries out identification to the video image and obtains the corresponding micro- table of the micro- expression of face in the video image
Feelings type and the corresponding instantaneous confidence level of micro- expression type；
It should be noted that the micro- expression model of product degree of recognition can identify video image, 54 kinds can be obtained
Micro- expression type, as shown in Table I, micro- expression type includes love, interested, pleasantly surprised, expectation ... is aggressive, conflict, humiliates, bosom
It doubts and fear waits 54 kinds of micro- expression types.It is a certain micro- that the corresponding instantaneous confidence level of micro- expression type refers to that the micro- expression of face belongs to
The probability of expression type, and interface returns to the micro- expression confidence rate come and returns in real time, so referred to as instantaneous confidence rate.Example
Such as, it when being identified to a frame video image, recognizes the video image and belongs to the probability of " love " this micro- expression type and be
0.9, then the instantaneous confidence level for belonging to " love " this micro- expression type is 0.9, and belongs to the general of " suspection " this micro- expression type
Rate is 0.05, then the instantaneous confidence level for belonging to " suspection " is 0.05.
Specifically, after getting the video image in the product introduction period, the micro- expression model of product degree of recognition will be right
Video image identified, the corresponding micro- expression type of the micro- expression of face of each frame image in video image and micro- expression
The corresponding instantaneous confidence level of type.
Specifically, referring to figure 3., Fig. 3 is to carry out identification to the video image in the embodiment of the present invention to obtain the view
The corresponding micro- expression type of the micro- expression of face and the step of micro- expression type corresponding instantaneous confidence level in frequency image
Process refinement schematic diagram, based on the above embodiment, step S200 includes:
Step S210 carries out identification to the video image and obtains the corresponding micro- table of the micro- expression of face in the video image
Feelings feature；
It is understood that each micro- expression type is all corresponding with specific micro- expressive features, therefore, view is being got
After frequency image, video image is identified, obtains the corresponding micro- expressive features of the micro- expression of face in each frame video image.
Step S220 obtains corresponding micro- expression type according to micro- expressive features and micro- expression type is corresponding
Instantaneous confidence level.
After obtaining micro- expressive features, the corresponding micro- expression type of the available micro- expressive features, while identifying this
The micro- expression of face belongs to the probability of micro- expression type.It should be noted that in identification process, if being not present in video image
Specific micro- expressive features then identify that the probability of micro- expression type corresponding with the specific micro- expressive features (is instantaneously set
Reliability) it is 0, that is, without considering during subsequent analysis.
Step S300 obtains corresponding related coefficient according to micro- expression type；
Specifically, it is previously provided with micro- expression information table in the terminal, it is as shown in Table I, corresponding getting video image
After micro- expression type, corresponding related coefficient can be found in micro- expression information table, related coefficient refers to video image pair
The degree of correlation of micro- expression type for answering and potential customers to the investment willingness of product.Related coefficient is specially Pearson correlation
Whether on one wire coefficient (Pearson CorrelationCoefficient) is to close face for measuring two datasets, it
For measuring the linear relationship between spacing variable.In the present embodiment, the value of related coefficient in [- 1,1], related coefficient it is absolute
Value is bigger, and correlation is stronger；That is, related coefficient is closer to 1 or -1, the degree of correlation is stronger；Related coefficient is related closer to 0
It spends weaker.Pass through the correlation intensity of following value range judgment variable under normal conditions: related coefficient 0.8-1.0 indicates extremely strong phase
It closes；Related coefficient 0.6-0.8 indicates strong correlation；Related coefficient 0.4-0.6 indicates moderate correlation；Related coefficient 0.2-0.4
Indicate weak correlation；Related coefficient 0.0-0.2 indicates extremely weak related or without correlation.
Table I: micro- expression information table
Wherein, in micro- expression information table, 54 kinds of micro- expressions are divided into positive classification, passive classification, between positive class
(i.e. micro- expression type is personality descriptor and neutral words to weak related category between other and passive classification, and positive classification refers to pair
Investment willingness degree has a positive effect and strong associations: such as (liking Love), (happy joy), (optimistic optimism) (trusts
Tust), (acceptable acceptance), (pleasantly surprised surprise) etc.；Passive classification, which refers to, plays negative consequence to investment willingness degree
And strong associations: as (absent-minded distraction), (contradict disobey Defiance), (Apprehension with a worried frown),
(sad sadness), (vexatious tired mesh Annoyance)；Weak related category refers to the neutrality that general action is played to investment willingness degree
Associations.
The instantaneous confidence level and the related coefficient are inserted investment willingness degree formula, obtain product wink by step S400
Between degree of recognition；
Specifically, after getting the corresponding instantaneous confidence rate of micro- expression type and micro- expression type corresponds to related coefficient,
Instantaneous confidence level and related coefficient are inserted into investment willingness degree formula, obtain the product moment degree of recognition of product.Since product is recognized
It is a value model that micro- expression model, which can be spent, to recognize the micro- expression value of product degree of recognition of facial image in each frame video image
It encloses for the score of [- 1,1], and interface returns to the micro- expression confidence rate come and returns in real time, so this score is also user
To an instant value of the degree of recognition of the product, referred to as product moment degree of recognition.
Wherein, investment willingness degree formula isWherein, piRefer to the corresponding related coefficient of micro- expression type i,
qiRefer to the corresponding moment instantaneous confidence level of micro- expression type i, R refers to product moment degree of recognition.
For example, " love " and " suspection " both micro- expression types have been recognized when identifying to a frame video image,
Also, recognize the video image belong to " love " this micro- expression type instantaneous confidence level be 0.9, and belong to " suspection " this
The instantaneous confidence level of micro- expression type is 0.05, and by inquiry, the corresponding related coefficient of " love " this micro- expression type is 1, " is cherished
Doubt " the corresponding related coefficient of this micro- expression type is -0.5, then, under the video image, product wink of the client to product
Between degree of recognition are as follows: R=0.9*1+0.05* (- 0.5)=0.875.
Furthermore, it is possible in terminal pre-set product degree of recognition grade, when the product moment degree of recognition of user is [0.8,1],
Corresponding product degree of recognition grade is very high；When the product moment degree of recognition of user is [0.3,0.8], corresponding product is approved
It is higher for spending grade；When the product moment degree of recognition of user is [- 0.8,0.3], corresponding product degree of recognition grade is lower；
When the product moment degree of recognition of user is [- 1, -0.8], corresponding product degree of recognition grade is very low.
Step S500 obtains client to the approval journey of product according to the product moment degree of recognition in the product introduction period
Degree.
It, can be according to all product moments after obtaining all product moment degrees of recognition in the product introduction period
Degree of recognition can obtain client to the degree of recognition of product.
Specifically, referring to figure 4., Fig. 4 is to be recognized in the embodiment of the present invention according to the product moment in the product introduction period
The process refinement schematic diagram for the step of degree of recognition of the acquisition client to product can be spent, based on the above embodiment, step S500 packet
It includes:
Step S510, product moment degree of recognition of the single client to product in the acquisition product introduction period；
Specifically, in order to obtain single client to the degree of recognition of single product, in the available product introduction period
Product moment degree of recognition of the single client to product.
Step S520 draws out in the product introduction period single client to product according to the product moment degree of recognition
Micro- expression trend graph；
Specifically, single client is drawn out in the product introduction period to production according to the moment degree of recognition of the product got
Micro- expression trend graph of product, the abscissa of micro- expression trend graph indicate the time, and ordinate indicates product moment degree of recognition, by micro-
Expression trend graph is clear that micro- expression shape change situation of the client during business personnel's products Presentation.
Step S530 obtains single client to the degree of recognition grade of product according to micro- expression trend graph.
Specifically, after drawing out micro- expression trend graph, according to tendency it can be concluded that client is to the degree of recognition etc. of product
Grade.In the product introduction period, the product moment degree of recognition major part integrated distribution of user is at [0.8,1], then the user
It is very high to the product degree of recognition of the product；In the product introduction period, the product moment degree of recognition of user is largely concentrated
When being distributed in [0.3,0.8], then the user is higher to the product degree of recognition of the product；In the product introduction period, user
Product moment degree of recognition major part integrated distribution at [- 0.8,0.3], then the user to the product degree of recognition of the product compared with
It is low；In the product introduction period, the product moment degree of recognition major part integrated distribution of user is at [- 1, -0.8], then the use
Family is very low to the product degree of recognition of the product.
In technical solution of the present invention, the video image in the product introduction period is obtained；Identification is carried out to video image to obtain
Take the corresponding micro- expression type of the micro- expression of face and the corresponding instantaneous confidence level of micro- expression type in video image；According to micro- table
Feelings type obtains corresponding related coefficient；Instantaneous confidence level and related coefficient are inserted into investment willingness degree formula, obtain product wink
Between degree of recognition；Client is obtained to the degree of recognition of product according to the product moment degree of recognition in the product introduction period.The present invention
The technical solution of proposition is based on micro- Expression Recognition and identifies to the micro- expression of face in video image, will be corresponding with micro- expression type
Instantaneous confidence level and related coefficient insert investment willingness degree formula, obtain product moment degree of recognition, and recognize according to product moment
It can spend and obtain client to the degree of recognition of product, the marketing of financial business personnel's reasonable disposition more preferably can more accurately be instructed to live
It is dynamic.The present invention can obtain client to the degree of recognition of product by being identified to video image, can be improved and recognize product
The analysis efficiency that can be spent.
Further, referring to figure 5., Fig. 5 is that the process of product of the present invention degree of recognition analysis method second embodiment is illustrated
Figure, based on the above embodiment, after step S520, further includes:
Art is talked about in step S521, the sale obtained in the product introduction period；
Specifically, various situations of the business personnel to client's products Presentation within the product introduction period, wherein be designed into
Art (topic) is talked about in various sale, for example, needing product feature in products Presentation A, income is popularized, risk is universal, product is special
The sale such as introduction, conclusion words art is expanded in color, intention inquiry.After drawing out micro- expression trend graph of client, obtains product and be situated between
The sale words art to continue in the period.
Step S522 obtains micro- expression tendency of product under each sale words art according to micro- expression trend graph of product；
Specifically, it is postoperative that sale words are got, the period that art is talked about in sale are said according to business personnel, in micro- expression tendency
The corresponding period is found in figure, in the micro- expression tendency for obtaining the client in the corresponding period, that is, obtain each sale and talk about art
Micro- expression tendency of lower product, so that the product moment degree of recognition for helping business personnel quickly to rest in client under sale words art becomes
Change trend.
Step S523 obtains crucial words art according to micro- expression tendency of product under each sale words art, and by the key
Words art is added to intelligence words art library.
It, will be corresponding in the period of micro- expression tendency rising in the case where obtaining each sale words art after micro- expression tendency of product
Sale words art as crucial words art, that is, corresponding sale words art in the period for rising the product moment degree of recognition of client
Art is talked about as key, then key words art is added to intelligence words art library.The crucial words art that client's degree of recognition will be promoted adds
Add to intelligence words art library, allow business personnel according to the crucial words art in intelligence words art library to adjust in time sale words art with
Service quality reaches sale intention with this.That is, talking about art library by intelligence talks about art come back feeding business personnel itself, to promote industry
The sales level of business personnel, saves business personnel and talks about art training input cost, also removes client and pays a return visit a large amount of manpower and material resources costs.
Further, Fig. 6 is please referred to, Fig. 6 is that the process of product of the present invention degree of recognition analysis method 3rd embodiment is illustrated
Figure, based on the above embodiment, after step S530, further includes:
Step S540, degree of recognition grade of all clients to identical product in the acquisition product introduction period；
Specifically, product degree of recognition grade is divided into very high, higher, lower and very low, is obtained by micro- expression trend graph
After single client is to the degree of recognition grade of product, all clients in the terminal available product introduction period are to same production
The degree of recognition grade of product, for example, acquisition business personnel is promoted all when the product of introduction has tri- kinds of A, B, C
Client is to the degree of recognition grade of A, the degree of recognition grade to B and the degree of recognition grade to C.
Step S550 counts client's number of different product degree of recognition grades；
Specifically, after getting all clients to the degree of recognition grade of identical product, different product degrees of recognition is counted
Client's number under grade, that is, when statistical product degree of recognition grade is respectively very high, higher, lower, very low, each product is approved
Spend client's number under grade.
Step S560 obtains market to the degree of recognition of identical product according to client's number.
Specifically, after obtaining client's number under different product degree of recognition grades, according to each product degree of recognition etc.
Client's number under grade may determine that whole market is very high client to the degree of recognition of the product, such as fruit product degree of recognition grade
Number at most, illustrates that whole market is very high to the degree of recognition of product；If fruit product degree of recognition grade is that higher client's number is most, say
Bright whole market is higher to the degree of recognition of product；If fruit product degree of recognition grade is that lower client's number is most, illustrate entire city
Field is lower to the degree of recognition of product；If fruit product degree of recognition grade is that very low client's number is most, illustrate whole market to product
Degree of recognition it is very low.
Further, Fig. 7 is please referred to, Fig. 7 is that the process of product of the present invention degree of recognition analysis method fourth embodiment is illustrated
Figure is based on first embodiment, after step S530, further includes:
Step S570, degree of recognition grade of the single client to different product in the acquisition product introduction period；
Specifically, can to business personnel to client's products Presentation when video image carry out identification obtain client product
Moment degree of recognition, therefore, the video image that can be described different product to same client identify, are situated between in same client
Continue different product video image all identification after, degree of recognition grade of the available single client to different product.
Step S580 draws out single client to different product according to degree of recognition grade of the single client to different product
Preference distribution figure；
After getting single client to the degree of recognition grade of different product, different product is recognized according to single client
Can intensity grade draw out single client to the preference distribution figure of different product, the abscissa of distribution map is the type of product, is indulged
Coordinate is product degree of recognition grade.
Step S590 obtains the product preference of client according to the preference distribution figure.
Specifically, after having drawn preference distribution figure, in preference distribution figure, the degree of recognition higher grade, illustrates client
The corresponding product of degree of recognition grade is more approved, therefore, the product that client can be directly obtained by product preference figure is inclined
Good attribute.
In addition, in another embodiment, all clients can also be obtained to the product degree of recognition grade of different product, incited somebody to action
All clients distinguish according to the age, obtain product degree of recognition grade of the client to different product of all ages and classes.For example, needle
To A product, product degree of recognition grade of the client to A product of all ages and classes is obtained, counts visitor under different product degree of recognition grade
The age distribution situation at family, the product degree of recognition grade to A product are the ratio of the client of which age bracket in very high client
At most, illustrate that A product compares to be liked by the age bracket.
Further, when establishing the micro- expression model of product degree of recognition, micro- facial expression image sample can be first acquired, by micro- table
Feelings image pattern is input to the micro- expression model of product degree of recognition, in original micro- Expression Recognition model by the micro- expression interface of Gamma
Feature extraction, cluster are carried out to micro- facial expression image sample and related coefficient is set, generates investment willingness degree formula.Meanwhile having
When data, by convolutional neural networks training client to the micro- expression model of the product degree of recognition of financial product degree of recognition, constantly entangle
Accuracy is continuously improved in positive formula.The correction procedure of model formation is the product based on the practical user for carrying out product purchase
Approve micro- expression Value Data (illustrating that product degree of recognition is very high) and do not buy the client of product (explanation is very low to product degree of recognition)
Product approve micro- expression Value Data and expression picture, get the corresponding instantaneous confidence rate of the micro- expression type of reality of return,
Then optimization back feeding is adjusted to the related coefficient in formula, improves the accuracy of model.
In addition, please referring to Fig. 8, the present invention also provides a kind of product degree of recognition analytical equipment 10, the product degrees of recognition point
Analysis apparatus 10 includes:
First obtains mould, and 20, described first, which obtains module, is used to obtain the video image in the product introduction period；
Identification module 30, the identification module are used to carry out the video image identification to obtain people in the video image
The corresponding micro- expression type of the micro- expression of face and the corresponding instantaneous confidence level of micro- expression type；
Second obtains module 40, and described second, which obtains module, is used to obtain corresponding phase relation according to micro- expression type
Number；
Computing module 50, the computing module are used to the instantaneous confidence level and the related coefficient inserting investment willingness
Formula is spent, product moment degree of recognition is obtained；
Third obtains module 60, and the third obtains module and is used to be approved according to the product moment in the product introduction period
Degree obtains client to the degree of recognition of product.
Further, the third obtains module 60 and is also used to:
Product moment degree of recognition of the single client to product in the acquisition product introduction period；
Single client in the product introduction period is drawn out according to the product moment degree of recognition to walk micro- expression of product
Gesture figure；
Single client is obtained to the degree of recognition grade of product according to micro- expression trend graph.
Further, the product degree of recognition analytical equipment 10 further include:
4th obtains module, and the 4th acquisition module is used to obtain the sale words art in the product introduction period；
5th obtains module, and the described 5th, which obtains module, is used to obtain each sale words according to micro- expression trend graph of product
Micro- expression tendency of product under art；
Adding module, the adding module are used to obtain crucial words according to micro- expression tendency of product under each sale words art
Art, and the crucial words art is added to intelligence words art library.
Further, the product degree of recognition analytical equipment 10 further include:
6th obtains module, and the 6th acquisition module is for obtaining in the product introduction period all clients to same production
The degree of recognition grade of product；
Statistical module, the statistical module are used to count client's number of different product degree of recognition grades；
7th obtains module, and the 7th acquisition module, which is used to obtain market according to client's number, recognizes identical product
It can degree.
Further, the product degree of recognition analytical equipment 10 further include:
8th obtains module, and the 8th acquisition module is for obtaining in the product introduction period single client to different productions
The degree of recognition grade of product；
Drafting module, the drafting module are used to draw out list according to degree of recognition grade of the single client to different product
Preference distribution figure of a client to different product；
9th obtains module, and the product that the 9th acquisition module is used to obtain client according to the preference distribution figure is inclined
It is good.
Further, the identification module 30 is also used to:
Identification is carried out to the video image and obtains the corresponding micro- expressive features of the micro- expression of face in the video image；
Corresponding micro- expression type is obtained according to the micro- expressive features and micro- expression type is corresponding instantaneously sets
Reliability.
Wherein, modules and the said goods degree of recognition analysis method embodiment in the said goods degree of recognition analytical equipment 10
In each step it is corresponding, function and realization process no longer repeat one by one here.
In addition, the present invention also provides a kind of computer readable storage mediums.
Product degree of recognition analysis program is stored on computer readable storage medium of the present invention, wherein product degree of recognition point
When analysis program is executed by processor, realize such as the step of above-mentioned product degree of recognition analysis method.
Wherein, product degree of recognition analysis program, which is performed realized method, can refer to the analysis of product of the present invention degree of recognition
Each embodiment of method, details are not described herein again.
It should be understood by those skilled in the art that, the embodiment of the present invention can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the present invention, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The present invention be referring to according to the method for the embodiment of the present invention, the process of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
It should be noted that in the claims, any reference symbol between parentheses should not be configured to power
The limitation that benefit requires.Word "comprising" does not exclude the presence of component or step not listed in the claims.Before component
Word "a" or "an" does not exclude the presence of multiple such components.The present invention can be by means of including several different components
It hardware and is realized by means of properly programmed computer.In the unit claims listing several devices, these are filled
Several in setting, which can be, to be embodied by the same item of hardware.The use of word first, second, and third is not
Indicate any sequence.These words can be construed to title.
Although preferred embodiments of the present invention have been described, it is created once a person skilled in the art knows basic
Property concept, then additional changes and modifications may be made to these embodiments.So it includes excellent that the following claims are intended to be interpreted as
It selects embodiment and falls into all change and modification of the scope of the invention.
The above description is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all at this
Under the inventive concept of invention, using equivalent structure transformation made by description of the invention and accompanying drawing content, or directly/use indirectly
It is included in other related technical areas in scope of patent protection of the invention.
Claims (10)
1. a kind of product degree of recognition analysis method, which is characterized in that the product degree of recognition analysis method includes:
Obtain the video image in the product introduction period；
Identification is carried out to the video image and obtains the corresponding micro- expression type of the micro- expression of face and institute in the video image
State the corresponding instantaneous confidence level of micro- expression type；
Corresponding related coefficient is obtained according to micro- expression type；
The instantaneous confidence level and the related coefficient are inserted into investment willingness degree formula, obtain product moment degree of recognition；
Client is obtained to the degree of recognition of product according to the product moment degree of recognition in the product introduction period.
2. product degree of recognition analysis method as described in claim 1, which is characterized in that the investment willingness degree formula isWherein, piRefer to the corresponding related coefficient of micro- expression type i, qiRefer to micro- expression type i corresponding wink moment
When confidence level, R refers to product moment degree of recognition.
3. product degree of recognition analysis method as described in claim 1, which is characterized in that described according in the product introduction period
Product moment degree of recognition obtain client and include: to the step of degree of recognition of product
Product moment degree of recognition of the single client to product in the acquisition product introduction period；
Single client is drawn out in the product introduction period to micro- expression trend graph of product according to the product moment degree of recognition；
Single client is obtained to the degree of recognition grade of product according to micro- expression trend graph.
4. product degree of recognition analysis method as claimed in claim 3, which is characterized in that described to be approved according to the product moment
Degree was drawn out after the step of micro- expression trend graph of single client in the product introduction period to product, further includes:
Art is talked about in the sale obtained in the product introduction period；
Micro- expression tendency of product under each sale words art is obtained according to micro- expression trend graph of product；
Crucial words art is obtained according to micro- expression tendency of product under each sale words art, and the crucial words art is added to intelligence
Talk about art library.
5. product degree of recognition analysis method as claimed in claim 3, which is characterized in that described according to micro- expression trend graph
After the step of obtaining degree of recognition grade of the single client to product, further includes:
Degree of recognition grade of all clients to identical product in the acquisition product introduction period；
Count client's number of different product degree of recognition grades；
Market is obtained to the degree of recognition of identical product according to client's number.
6. product degree of recognition analysis method as claimed in claim 3, which is characterized in that described according to micro- expression trend graph
After the step of obtaining degree of recognition grade of the single client to product, further includes:
Degree of recognition grade of the single client to different product in the acquisition product introduction period；
Single client is drawn out to the preference distribution figure of different product according to degree of recognition grade of the single client to different product；
The product preference of client is obtained according to the preference distribution figure.
7. such as product degree of recognition analysis method of any of claims 1-6, which is characterized in that described to the video
Image carries out identification and obtains the corresponding micro- expression type of the micro- expression of face and micro- expression type pair in the video image
The step of instantaneous confidence level answered includes:
Identification is carried out to the video image and obtains the corresponding micro- expressive features of the micro- expression of face in the video image；
Corresponding micro- expression type and the corresponding instantaneous confidence level of micro- expression type are obtained according to micro- expressive features.
8. a kind of product degree of recognition analytical equipment, which is characterized in that the product degree of recognition analytical equipment includes:
First obtains module, and the first acquisition module is used to obtain the video image in the product introduction period；
Identification module, the identification module are used to carry out the video image identification to obtain the micro- table of face in the video image
The corresponding micro- expression type of feelings and the corresponding instantaneous confidence level of micro- expression type；
Second obtains module, and described second, which obtains module, is used to obtain corresponding related coefficient according to micro- expression type；
Computing module, the computing module are used for the instantaneous confidence level and related coefficient filling investment willingness degree is public
Formula obtains product moment degree of recognition；
Third obtains module, and the third obtains module and is used to be obtained according to the product moment degree of recognition in the product introduction period
The degree of recognition of the client to product.
9. a kind of terminal, which is characterized in that including processor, memory and be stored on the memory can be described
The product degree of recognition that processor executes analyzes program, wherein when the product degree of recognition analysis program is executed by the processor,
The step of realizing the product degree of recognition analysis method as described in any one of claims 1 to 7.
10. a kind of computer readable storage medium, which is characterized in that be stored with product on the computer readable storage medium and recognize
Analysis program can be spent, wherein when the product degree of recognition analysis program is executed by processor, realize as appointed in claim 1 to 7
Described in one the step of product degree of recognition analysis method.
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| PCT/CN2020/086166 WO2020253363A1 (en) | 2019-06-19 | 2020-04-22 | Product approval degree analysis method and device, terminal and computer readable storage medium |
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019029261A1 (en) * | 2017-08-07 | 2019-02-14 | 深圳市科迈爱康科技有限公司 | Micro-expression recognition method, device and storage medium |
| CN109858958A (en) * | 2019-01-17 | 2019-06-07 | 深圳壹账通智能科技有限公司 | Aim client orientation method, apparatus, equipment and storage medium based on micro- expression |
| CN109858405A (en) * | 2019-01-17 | 2019-06-07 | 深圳壹账通智能科技有限公司 | Satisfaction evaluation method, apparatus, equipment and storage medium based on micro- expression |
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| US10049263B2 (en) * | 2016-06-15 | 2018-08-14 | Stephan Hau | Computer-based micro-expression analysis |
| CN109784312A (en) * | 2019-02-18 | 2019-05-21 | 深圳锐取信息技术股份有限公司 | Teaching Management Method and device |
| CN110415015A (en) * | 2019-06-19 | 2019-11-05 | 深圳壹账通智能科技有限公司 | Product degree of recognition analysis method, device, terminal and computer readable storage medium |
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| WO2019029261A1 (en) * | 2017-08-07 | 2019-02-14 | 深圳市科迈爱康科技有限公司 | Micro-expression recognition method, device and storage medium |
| CN109858958A (en) * | 2019-01-17 | 2019-06-07 | 深圳壹账通智能科技有限公司 | Aim client orientation method, apparatus, equipment and storage medium based on micro- expression |
| CN109858405A (en) * | 2019-01-17 | 2019-06-07 | 深圳壹账通智能科技有限公司 | Satisfaction evaluation method, apparatus, equipment and storage medium based on micro- expression |
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|---|---|---|---|---|
| WO2020253363A1 (en) * | 2019-06-19 | 2020-12-24 | 深圳壹账通智能科技有限公司 | Product approval degree analysis method and device, terminal and computer readable storage medium |
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