CN103854227A - Interpersonal relationship analyzing system and method - Google Patents
Interpersonal relationship analyzing system and method Download PDFInfo
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- CN103854227A CN103854227A CN201210523800.2A CN201210523800A CN103854227A CN 103854227 A CN103854227 A CN 103854227A CN 201210523800 A CN201210523800 A CN 201210523800A CN 103854227 A CN103854227 A CN 103854227A
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Abstract
The invention discloses an interpersonal relationship analyzing system and method. The interpersonal relationship analyzing method comprises the steps that preset pictures within each time segment are obtained from a storage of an electronic device; pictures comprising a first user and a second user are identified from the pictures within each time segment; the distance between the first user and the second user in each identified picture within each time segment is calculated, and then the interpersonal relationship measured value, within each time segment, of the first user and the second user is obtained; an interpersonal relationship tendency chart of the first user and the second user is drawn according to the interpersonal relationship measured values within the time segments. By the utilization of the interpersonal relationship analyzing system and method, the interpersonal relationship between the users within each time segment can be analyzed according to the pictures of the users.
Description
Technical field
The present invention relates to a kind of data analysis system and method, relate in particular to a kind of interpersonal relation analytic system and method.
Background technology
The rise of community network makes many users gladly share picture in network, existing community network system can allow user carry out picture uploading as Facebook or Google+, and automatic human face recognition friend's function is provided, and by friend's information (as name) label (Tag) in photo.Community user can utilize label to understand for which friend in which photograph, but the power that is related between certain friend can not be provided in community user and picture.Further, if user wants understanding and this friend's interpersonal relation trend (as good especially in which year relation), this user may have no idea to bring ...back at once, must manually go photo albums to select, and this process need expends a large amount of time.
Summary of the invention
In view of above content, be necessary to provide a kind of interpersonal relation analytic system and method, it can analyze the interpersonal relation between user in each time section according to user picture, and the interpersonal relation between user is depicted as to interpersonal relation trend map.
A kind of interpersonal relation analytic system, is applied to electronic installation, and this system comprises: photo acquisition module, for obtain the photo in default each time section from the storer of electronic installation; Face recognition module, identifies for the photo in each time section the photo that comprises first user and the second user; Interpersonal relation analysis module, for calculating respectively every photo first user identifying in each time section and the second user's distance, thereby obtains first user and the interpersonal relation metric of the second user in each time section; Interpersonal relation display module, for drawing out first user and the second user's interpersonal relation trend map according to the interpersonal relation metric in each time section, this interpersonal relation trend map comprises the change curve of first user and the interpersonal relation metric of the second user in each time section.
A kind of interpersonal relation analytical approach, is applied to electronic installation, and the method comprises: photo obtaining step obtains the photo in default each time section from the storer of electronic installation; Recognition of face step, identifies the photo that comprises first user and the second user the photo in each time section; Interpersonal relation analytical procedure one, calculates respectively the distance of first user and the second user in every the photo identifying in each time section, thereby obtains first user and the interpersonal relation metric of the second user in each time section; Interpersonal relation is shown step, draw out first user and the second user's interpersonal relation trend map according to the interpersonal relation metric in each time section, this interpersonal relation trend map comprises the change curve of first user and the interpersonal relation metric of the second user in each time section.
Compared to prior art, described interpersonal relation analytic system and method, it can analyze the interpersonal relation between user in each time section according to user picture, and the interpersonal relation between user is depicted as to interpersonal relation trend map, facilitate community user to check the development trend that is related between user.
Brief description of the drawings
Fig. 1 is the running environment schematic diagram of the interpersonal relationship analysis system of the present invention.
Fig. 2 is the functional block diagram of the interpersonal relationship analysis system of the present invention.
Fig. 3 is the process flow diagram of the preferred embodiment of the interpersonal relationship analysis method of the present invention.
Fig. 4 is the first user drawn out of the present invention and the second user's interpersonal relation trend map.
Fig. 5 is the schematic diagram of traveling time grid in the interpersonal relation trend map of drawing.
Fig. 6 is the schematic diagram that carries out many people inquiry.
Fig. 7 is first user and the strong and weak schematic diagram of the relation of the second user in different time section.
Fig. 8 is first user and the number of pictures schematic diagram of the second user in different time section.
Main element symbol description
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| Interpersonal relation |
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| Interpersonal |
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| Interpersonal |
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| Interpersonal |
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Embodiment
As shown in Figure 1, be the running environment schematic diagram of the interpersonal relationship analysis system of the present invention.This interpersonal relation analytic system 24 runs in electronic installation 2.This electronic installation 2 also comprises the display device 20 connected by data bus, input equipment 22, storer 23 and processor 25.Described electronic installation 2 can be computer, mobile phone, PDA(Personal Digital Assistant, personal digital assistant) etc.
Described storer 23 is for storing the data such as program code and user picture of described interpersonal relation analytic system 24.Described display device 20 is for showing the data such as described user picture and interpersonal relation trend map, for example, and LCDs, the touch-screen of mobile phone etc. that described display device 20 can be computer.The various data that described input equipment 22 arranges for inputting user, for example, this input equipment 22 comprises keyboard, mouse etc.
Described interpersonal relation analytic system 24 is for analyze the interpersonal relation between user in each time section according to user picture, and the interpersonal relation between user is depicted as to interpersonal relation trend map, is presented on display device 20, and detailed process is described below.
In the present embodiment, described interpersonal relation analytic system 24 can be divided into one or more modules, described one or more module is stored in described storer 23 and is configured to and carried out by one or more processors (the present embodiment is a processor 25), to complete the present invention.For example, consult shown in Fig. 2, described interpersonal relation analytic system 24 is divided into data reception module 240, photo acquisition module 241, face recognition module 242, interpersonal relation analysis module 243 and interpersonal relation display module 244.The alleged module of the present invention has been the program segment of a specific function, is more suitable in describing the implementation of software in electronic installation 2 than program.The concrete function of each module is described below with reference to Fig. 3.
As shown in Figure 3, be the process flow diagram of the preferred embodiment of the interpersonal relationship analysis method of the present invention.
Step S10, data reception module 240 receive first user input the second user keyword and for analyzing the size of time section of interpersonal relation.Described the second user's keyword can be this second user's title.In the present embodiment, first user is user, consults shown in Fig. 4, and first user (me) can be inputted the title (Celine) of the second user at community website (as Facebook) at search box.The size of described time section can be a week, one month, a season etc.
Step S11, photo acquisition module 241 obtains all photos in each time section from the photograph of storer 23 is thin.In the present embodiment, all photos of described photograph in thin all comprise the information of a shooting time.Particularly, if having EXIF(Exchangeable image fileformat, exchangeable image file format in a photo) information, be set as to the shooting time of this photo the time of recording in EXIF information.If there is no EXIF information in a photo, this photo upload is set as to the shooting time of this photo to the time of community website (as storer 23).
For example, the size of supposing first user setting-up time section is one month, and photo acquisition module 241 is according to the shooting time of each photo, obtains all photos of every month from the photograph of storer 23 is thin.For example, photo acquisition module 241 obtains 10 photos January in 2012, February 15 photos etc.In other embodiments, the size of described time section also can be set as default value (as 1 month), sets without user.
Step S12, identifies the photo that comprises first user and the second user all photos of face recognition module 242 in each time section.For example, face recognition module 242 identifies to be had 6 January in 2012 and comprises first user and the second user in 10 photos, have 8 February and comprise first user and the second user in 15 photos.
Particularly, face recognition module 242 identifies the face block in each photo in each time section, the above-mentioned face block identifying and first user and the second user's human face photo is compared, to judge whether this photo comprises first user and the second user.Wherein, first user and the second user's human face photo can be first user and the second user head portrait at community website.
If there is the first face block mating with the human face photo of first user in this photo, and the second face block mating with the second user's human face photo, face recognition module 242 judges that this photo comprises first user and the second user.
Step S13, interpersonal relation analysis module 243 calculates respectively the distance of first user and the second user in every the photo identifying in each time section, thereby obtains first user and the interpersonal relation metric of the second user in each time section.For example, interpersonal relation analysis module 243 calculates first user and the second user is 80 at the interpersonal relation metric in January, 2012, and the interpersonal relation metric in February is 90.Interpersonal relation metric in a time section is higher, represents that first user and the second user relation in this time section is better.
Particularly, interpersonal relation analysis module 243 obtains every photo in each time section successively, calculates according to the face number of blocks comprising in every photo the number U that every photo comprises.
Interpersonal relation analysis module 243 calculates the distance B between first user and the second user in every photo.Described distance refers to interpersonal adjacent degree in photo.For example, if in a certain photo, two people are close to, and this two person-to-person distance is 1, if be separated by n people between these two people, this two person-to-person distance is n+1.
Interpersonal relation analysis module 243 is according to a default ralation method, utilizes number U in every photo and first user and the second user's distance B, calculates the relationship strength E between first user and the second user in every photo.Described ralation method is E=1/f (U, D), for example, and E=1/(U*D).
After all photo disposals in each time section, interpersonal relation analysis module 243 adds up every relationship strength E that photo calculates in this time section, to obtain first user and the second user interpersonal relation metric in each time section, computing method are as described in formula (1).
Wherein, E
tt(a, b) represents that first user a and the second user b are in time section T
tinterior interpersonal relation metric.
P
ttbe illustrated in this time section T
tin, the photo sum that comprises first user and the second user.
U
nbe illustrated in this time section T
tinterior n opens the number that photo comprises.
D
n(a, b) is illustrated in this time section T
tin n open the distance between first user a and the second user b in photo.
Step S14, interpersonal relation display module 244 is drawn out interpersonal relation trend Figure 30 of first user and the second user according to the interpersonal relation metric in each time section, and this interpersonal relation trend Figure 30 is presented on display device 20.Consult shown in Fig. 4, this interpersonal relation trend Figure 30 comprises the change curve L1 of first user and the interpersonal relation metric of the second user in each time section.Wherein, the transverse axis of this interpersonal relation trend Figure 30 represents the time, and the every bit in transverse axis represents a time section T
t, for example, T
t1represent in January, 2004, i.e. [2004-01-01,2004-01-31], the longitudinal axis represents first user and the second user interpersonal relation metric E in each time section
tt.From can visually see first user and the second user's the development trend that is related to of the curve L1 of Fig. 4, for example, when relation is best, when starts slowly to become and become estranged.
In other embodiments, this interpersonal relation trend Figure 30 can also comprise a movably time grid 32, and this time grid 32 comprises the photo that comprises first user and the second user identifying in multiple time sections and each time section.Consult shown in Fig. 4, this time grid 32 comprises time section T
t1to time section T
t1-n.Consult shown in Fig. 5, the time grid 32 after moving comprises time section T
t2to time section T
t2-n.In the time that this time grid 32 moves, interpersonal relation display module 244 is according to predetermined order (as shooting time order), and the photo that interior this time grid 32 each time section is identified is presented at the below of interpersonal relation trend Figure 30.In other embodiments, the width of described time grid 32 can expand or dwindle, and minimum can become straight line (i.e. a time section).
In other embodiments, data reception module 240 also can receive the second user and the 3rd user's of first user input keyword (even more keyword), and wherein, first user is user.Consult shown in Fig. 6, first user (me) can be inputted the second user's title (Celine) and the 3rd user's title (Mandy) at search box.In interpersonal relation trend Figure 30, will show two relation curves, wherein, Article 1 relation curve L1 represents first user and the second user's interpersonal relation trend, and Article 2 relation curve L2 represents first user and the 3rd user's interpersonal relation trend.
It should be noted that, in other embodiments, when data reception module 240 receives after the second user of first user input and the 3rd user's keyword, also can only in interpersonal relation trend Figure 30, show the second user and the 3rd user's relation curve.
In other embodiments, step S13 can be also: interpersonal relation analysis module 243, according to the number of pictures that comprises first user and the second user identifying in each time section, is determined first user and the second user interpersonal relation metric in each time section.The number of pictures identifying in a time section is more, and definite interpersonal relation metric is higher, represents that first user and the second user relation in this time section is better.
But, determine that by number of pictures the accuracy of interpersonal relation metric is less than the accuracy of determining interpersonal relation metric by relationship strength (being user distance).For example, consult shown in Fig. 7 time section T
t-1interpersonal relation metric E
tt-1be less than time section T
t-2interpersonal relation metric E
tt-2.But consult shown in Fig. 8 time section T
t-1interior number of pictures P
tt-1will be more than time section T
t-2number of pictures P
tt-2.Nogata bar representative picture quantity in Fig. 8, the higher representative picture quantity of Nogata bar is more.
Finally it should be noted that, above embodiment is only unrestricted in order to technical scheme of the present invention to be described, although the present invention is had been described in detail with reference to preferred embodiment, those of ordinary skill in the art is to be understood that, can modify or be equal to replacement technical scheme of the present invention, and not depart from the spirit and scope of technical solution of the present invention.
Claims (20)
1. an interpersonal relation analytic system, is applied to electronic installation, it is characterized in that, this system comprises:
Photo acquisition module, for obtaining the photo in default each time section from the storer of electronic installation;
Face recognition module, identifies for the photo in each time section the photo that comprises first user and the second user;
Interpersonal relation analysis module, for calculating respectively every photo first user identifying in each time section and the second user's distance, thereby obtains first user and the interpersonal relation metric of the second user in each time section; And
Interpersonal relation display module, for drawing out first user and the second user's interpersonal relation trend map according to the interpersonal relation metric in each time section, this interpersonal relation trend map comprises the change curve of first user and the interpersonal relation metric of the second user in each time section.
2. interpersonal relation analytic system as claimed in claim 1, is characterized in that, every photo in this storer all comprises the information of a shooting time.
3. interpersonal relation analytic system as claimed in claim 2, it is characterized in that, if have EXIF information in a photo, be set as to the shooting time of this photo the time of recording in EXIF information, if there is no EXIF information in a photo, this photo upload is set as to the shooting time of this photo to the time of storer.
4. interpersonal relation analytic system as claimed in claim 1, is characterized in that, identifies the photo that comprises first user and the second user and comprise the photo of described face recognition module in each time section:
Identify the face block in each photo in each time section, the above-mentioned face block identifying and first user and the second user's human face photo is compared;
If there is the first face block mating with the human face photo of first user in a photo, and the second face block mating with the second user's human face photo, judge that this photo comprises first user and the second user.
5. interpersonal relation analytic system as claimed in claim 1, is characterized in that, described interpersonal relation analysis module obtains first user and the interpersonal relation metric of the second user in each time section comprises:
Obtain successively every photo in each time section, calculate according to the face number of blocks comprising in every photo the number U that every photo comprises;
Calculate the distance B between first user and the second user in every photo;
According to default ralation method E=1/f(U, a D), utilize number U in every photo and first user and the second user's distance B, calculate the relationship strength E between first user and the second user in every photo; And
Add up every relationship strength E that photo calculates in each time section, to obtain first user and the second user interpersonal relation metric in each time section.
6. interpersonal relation analytic system as claimed in claim 5, it is characterized in that, distance B between described first user and the second user is determined according to following methods: if be separated by n people between first user and the second user, determine that the distance between first user and the second user is n+1.
7. interpersonal relation analytic system as claimed in claim 5, is characterized in that, described ralation method is E=1/(U*D).
8. interpersonal relation analytic system as claimed in claim 1, it is characterized in that, described interpersonal relation trend map also comprises a movably time grid, in the time that this time, grid moved, according to predetermined order, the photo identifying in each time section of this time grid is presented to the below of interpersonal relation trend map.
9. interpersonal relation analytic system as claimed in claim 8, is characterized in that, the width of described time grid can expand or dwindle.
10. interpersonal relation analytic system as claimed in claim 1, is characterized in that, described interpersonal relation analysis module also for:
According to the number of pictures that comprises first user and the second user identifying in each time section, determine first user and the second user interpersonal relation metric in each time section.
11. 1 kinds of interpersonal relation analytical approachs, are applied to electronic installation, it is characterized in that, the method comprises:
Photo obtaining step obtains the photo in default each time section from the storer of electronic installation;
Recognition of face step, identifies the photo that comprises first user and the second user the photo in each time section;
Interpersonal relation analytical procedure one, calculates respectively the distance of first user and the second user in every the photo identifying in each time section, thereby obtains first user and the interpersonal relation metric of the second user in each time section; And
Interpersonal relation is shown step, draw out first user and the second user's interpersonal relation trend map according to the interpersonal relation metric in each time section, this interpersonal relation trend map comprises the change curve of first user and the interpersonal relation metric of the second user in each time section.
12. interpersonal relation analytical approachs as claimed in claim 11, is characterized in that, every photo in this storer all comprises the information of a shooting time.
13. interpersonal relation analytical approachs as claimed in claim 12, it is characterized in that, if have EXIF information in a photo, be set as to the shooting time of this photo the time of recording in EXIF information, if there is no EXIF information in a photo, this photo upload is set as to the shooting time of this photo to the time of storer.
14. interpersonal relation analytical approachs as claimed in claim 11, is characterized in that, described recognition of face step comprises:
Identify the face block in each photo in each time section, the above-mentioned face block identifying and first user and the second user's human face photo is compared;
If there is the first face block mating with the human face photo of first user in a photo, and the second face block mating with the second user's human face photo, judge that this photo comprises first user and the second user.
15. interpersonal relation analytical approachs as claimed in claim 11, is characterized in that, described interpersonal relation analytical procedure one comprises:
Obtain successively every photo in each time section, calculate according to the face number of blocks comprising in every photo the number U that every photo comprises;
Calculate the distance B between first user and the second user in every photo;
According to default ralation method E=1/f(U, a D), utilize number U in every photo and first user and the second user's distance B, calculate the relationship strength E between first user and the second user in every photo; And
Add up every relationship strength E that photo calculates in each time section, to obtain first user and the second user interpersonal relation metric in each time section.
16. interpersonal relation analytical approachs as claimed in claim 15, it is characterized in that, distance B between described first user and the second user is determined according to following methods: if be separated by n people between first user and the second user, determine that the distance between first user and the second user is n+1.
17. interpersonal relation analytical approachs as claimed in claim 15, is characterized in that, described ralation method is E=1/(U*D).
18. interpersonal relation analytical approachs as claimed in claim 11, it is characterized in that, described interpersonal relation trend map also comprises a movably time grid, in the time that this time, grid moved, according to predetermined order, the photo identifying in each time section of this time grid is presented to the below of interpersonal relation trend map.
19. interpersonal relation analytical approachs as claimed in claim 18, is characterized in that, the width of described time grid can expand or dwindle.
20. interpersonal relation analytical approachs as claimed in claim 11, is characterized in that, the method also comprises:
Interpersonal relation analytical procedure two, according to the number of pictures that comprises first user and the second user identifying in each time section, determines first user and the second user interpersonal relation metric in each time section.
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| CN106980644A (en) * | 2017-02-20 | 2017-07-25 | 浙江大学 | A kind of individual interpersonal relationships visual inference method of isomery Urban Data |
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