CN111414883A - Program recommendation method, terminal and storage medium based on face emotion - Google Patents
Program recommendation method, terminal and storage medium based on face emotion Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/174—Facial expression recognition
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- G—PHYSICS
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/174—Facial expression recognition
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/441—Acquiring end-user identification, e.g. using personal code sent by the remote control or by inserting a card
- H04N21/4415—Acquiring end-user identification, e.g. using personal code sent by the remote control or by inserting a card using biometric characteristics of the user, e.g. by voice recognition or fingerprint scanning
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- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
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- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
- H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
- H04N21/4668—Learning process for intelligent management, e.g. learning user preferences for recommending movies for recommending content, e.g. movies
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- H04N21/47—End-user applications
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Abstract
The invention discloses a program recommendation method, a terminal and a storage medium based on face emotion, wherein the program recommendation method based on face emotion comprises the following steps: acquiring facial expressions of a user through a camera, and carrying out facial emotion analysis on the facial expressions; determining the current emotion of the user according to the analysis result, and matching the corresponding recommended program from a local program library or a network program library of the current application program; recommending the recommended program to the user through a push message, and carrying out top setting display on the recommended program in an application interface. The invention identifies the face emotion of the user through the camera, and matches the adaptive television program or music program according to the current emotion of the user, thereby recommending the appropriate television program or music program to the user, adjusting the current emotion of the user and avoiding further activation of the emotion of the user.
Description
Technical Field
The invention relates to the field of terminal application, in particular to a program recommendation method based on human face emotion, a terminal and a storage medium.
Background
Different people have different hobbies, even the same person, and have different hobbies in different periods, for example, the person likes watching animation in a small day and likes watching comprehensive programs in a long day; however, the human mood is changeable, sometimes excited, sometimes depressed, sometimes sad, and the excessive mood is unfavorable for the physical and mental health of the human.
For watching television programs, there are various types such as comprehension, sports, natural science, comedy, history, swordsmen, horror, and story; different programs (or music) have different excitatory effects on human emotions, for example, watching comedy while exciting, the more exciting; when the user is sad, the user is more sad when watching tragedies; the television is used as a central device for home entertainment, and recommending proper television programs (or music) is helpful for adjusting the emotion of the user and promoting the physical and mental health of the user.
Corresponding to traditional television applications or music applications, recommended television programs or music are popular categories at present, but the recommended television programs or music are not necessarily suitable for the emotion of the user and are not necessarily favorite categories of the user; therefore, it is necessary to recommend a television program or music suitable for the emotion of the user when watching the television program or listening to the music, in order to avoid further activation of the emotion of the user.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a program recommendation method, a terminal and a storage medium based on human face emotion, which can enable a user to selectively switch to a video original sound state and play video original sound content by retaining the original sound of a shot short video and hiding the original sound.
The technical scheme adopted by the invention for solving the technical problem is as follows:
in a first aspect, the present invention provides a program recommendation method based on human face emotion, where the program recommendation method based on human face emotion includes the following steps:
acquiring facial expressions of a user through a camera, and carrying out facial emotion analysis on the facial expressions;
determining the current emotion of the user according to the analysis result, and matching the corresponding recommended program from a local program library or a network program library of the current application program;
recommending the recommended program to the user through a push message, and carrying out top setting display on the recommended program in an application interface.
Further, the method for analyzing the facial emotion of the user by the camera comprises the following steps:
and setting the local program library in the current application program in advance.
Further, the method for obtaining the facial expression of the user through the camera and analyzing the facial emotion of the facial expression specifically comprises the following steps:
when the current application program is started, the position of the face is obtained through the camera;
and dynamically capturing and analyzing the eyebrow, the catch, the facial muscles and the mouth shape according to the position of the face.
Further, the determining the current emotion of the user according to the analysis result and matching the corresponding recommended program from the local program library or the network program library of the current application program specifically includes the following steps:
determining a current mood of the user according to a result of the dynamic capture analysis;
detecting the type of the current application program, and searching the local program library or the network program library according to the type;
matching the current emotion with programs in the local program library, or matching the current emotion with programs in the network program library;
and setting the matched program as the recommended program.
Further, the setting of the matched program as the recommended program specifically includes the following steps:
sorting the matched programs according to the matched similarity;
and setting the sequenced programs as the recommended programs.
Further, the recommending the recommended program to the user through the push message and displaying the recommended program on top in an application interface specifically includes the following steps:
sending the recommended program to an associated account of the user through the push message;
and displaying the recommended program in a program display area of the application interface, and carrying out set-top display on the recommended program.
Further, the recommending the recommended program to the user through the push message and displaying the recommended program on top in an application interface further includes:
and inquiring programs which are watched and not matched with the current emotion, and shielding or displaying the programs which are not matched.
Further, the current application programs include a television application and a music application, and the recommended programs include television programs and music programs.
In a second aspect, the present invention further provides a terminal, which includes a processor, and a memory connected to the processor, where the memory stores a program recommendation program based on facial emotion, and the program recommendation program based on facial emotion is used to implement the operations of the program recommendation method based on facial emotion according to the first aspect when executed by the processor.
In a third aspect, the present invention further provides a storage medium, where the storage medium stores a program recommendation program based on human face emotion, and the program recommendation program based on human face emotion is used to implement the operations of the program recommendation method based on human face emotion according to the first aspect when executed by a processor.
The invention adopts the technical scheme and has the following effects:
the invention identifies the face emotion of the user through the camera, and matches the adaptive television program or music program according to the current emotion of the user, thereby recommending the appropriate television program or music program to the user, adjusting the current emotion of the user and avoiding further activation of the emotion of the user.
Drawings
Fig. 1 is a flowchart of a program recommendation method based on human face emotion in an embodiment of the present invention.
Fig. 2 is a flow chart of recommending television programs in an embodiment of the present invention.
Fig. 3 is a flowchart of recommending music programs in an embodiment of the present invention.
Fig. 4 is a functional schematic diagram of a terminal in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example one
In the existing television applications (e.g., the arcade), and music applications (e.g., the internet and the internet), corresponding recommendations are generally made according to television programs or music watched by a user, so as to recommend the recently popular television programs or music to the user, thereby facilitating the use of the user; however, these recommendation methods are all based on broadcasting tv programs or music hotly as recommendations, and the recommended tv programs or music are not necessarily preferred by the user, even if the tv programs or music preferred by the user are not necessarily suitable for the current emotion of the user (for example, the user is in a sad emotion, and the recommended tragedy is not suitable for the current emotion of the user), which may further stimulate the current emotion of the user.
In view of the above technical problems, this embodiment provides a program recommendation method based on human face emotion, which aims to identify human face emotion of a user through a camera, and match an adaptive television program or music program according to current emotion of the user, so as to recommend an appropriate television program or music program to the user, adjust current emotion of the user, and avoid further activation of emotion of the user.
As shown in fig. 1, in an implementation manner of this embodiment, the program recommendation method based on human face emotion includes the following steps:
and S100, acquiring the facial expression of the user through a camera, and carrying out facial emotion analysis on the facial expression.
In this embodiment, the program recommendation method based on human face emotion is applied to a terminal, where the terminal includes a television, a mobile terminal, a computer, and a device with a camera; the present embodiment mainly uses a television as an example, and explains the program recommendation method based on human face emotion.
In practical applications, the application programs applicable to the program recommendation method based on human face emotion include, but are not limited to: television applications and music applications, the recommended programs including but not limited to: a television program corresponding to the television application and a music program corresponding to the music application.
In this embodiment, before recommending a program to a user, a corresponding local program library needs to be set in an application program of the terminal; during specific setting, setting can be performed when the terminal installs the application program; for example, when the terminal installs a television application, a local television program library may be set in the database of the television application; when the terminal is provided with the music application, a local music program library can be set in the database of the music application; the purpose of setting up the local program library is to: and setting corresponding program categories in the local program library, and setting corresponding program lists for the program categories, so that when recommending programs to users, programs adapted to the current emotions of the users can be matched preferentially from the local program library and taken as recommendations, and the matching efficiency of the recommended programs is improved.
Certainly, in actual application, a corresponding network program library may be further set in the server of the application program, so that the network program library may be used as a second matching object; when the local program library does not match with the corresponding recommended program, the program which is suitable for the current emotion of the user can be matched from the network program library and used as the recommendation, so that the matching resource is expanded.
Namely, the step S100 is preceded by:
and S001, setting the local program library in the current application program in advance.
In this embodiment, after the local program library is set, when the terminal detects that the user starts an application program, a camera is started according to the operation of the user, and the current emotion of the user is identified by the camera.
Specifically, a corresponding recommended function option is set in an application interface of the application program, when the user selects the recommended function option, the terminal automatically starts the camera, and the position of the face is obtained through the camera; the purpose of acquiring the face position of the user is to: and focusing and shooting position adjustment are carried out according to the face position of the user, so that the whole face of the user is contained in the shot picture.
After the face position of the user is obtained, the terminal carries out dynamic capture analysis on the eyebrow, the catch, the face muscle and the mouth shape according to the position of the face; when the dynamic capture analysis is carried out, a plurality of pictures containing the face of the user can be shot, and the shot pictures are compared with the pictures of the emotion templates.
When the comparison is carried out, the individual comparison can be carried out according to a single comparison principle, namely, the eyebrow, the catch of eyes, the facial muscle and the mouth shape in each picture are individually compared, for example, the eyebrow in the shot picture is compared with the eyebrow in the standard emotion template, and the similarity between the shot eyebrow and the eyebrow in the emotion template is obtained; similarly, the similarity of the eye spirit, the facial muscles and the mouth shape can be obtained; after comparison, comprehensive analysis can be performed according to the similarity of the eyebrows, the catch of eyes, the facial muscles and the mouth shape, so that the current emotion of the user is determined.
Namely, the step S100 specifically includes the following steps:
step S110, when the current application program is started, the position of the face is obtained through the camera;
and step S120, dynamically capturing and analyzing the eyebrow, the catch, the facial muscles and the mouth according to the position of the face.
When the user uses the application program, the camera is started according to the operation of the user, the face of the user is shot by the camera, and the eyebrow, the eye spirit, the facial muscles, the mouth shape and other parts are subjected to motion capture analysis, so that which emotion the viewer is in excitation, sadness, depression, flat emotion and the like is analyzed, and the adaptive program is matched according to the emotion obtained by analysis conveniently and subsequently.
As shown in fig. 1, in an implementation manner of this embodiment, the program recommendation method based on human face emotion further includes the following steps:
and step S200, determining the current emotion of the user according to the analysis result, and matching the corresponding recommended program from the local program library or the network program library of the current application program.
In this embodiment, after performing dynamic capture analysis on the eyebrow, catch of eye, facial muscle and mouth shape, it may be determined which emotion the current emotion of the user is, at this time, the terminal may detect the type of the current application program, and search the local program library or the network program library according to the type; and then, matching the current emotion with the programs in the local program library, or matching the current emotion with the programs in the network program library to set the matched programs as the recommended programs.
Specifically, the terminal may determine the current emotion of the user from the result of the dynamic capture analysis (e.g., similarity of facial organs); then, the corresponding local program library or network program library is searched by detecting the type of the current application program.
In actual application, if the current application used by the user is a television application, searching a local television program library in the television application, searching program categories in the local television program library according to the current emotion of the user, and screening a plurality of television programs from a program list of the program categories to serve as recommended programs; and if the local television programs are not matched with the corresponding television programs, screening a plurality of television programs from the network television programs through the network to serve as recommended programs.
And if the current application used by the user is a music application, matching from the local music program library or the network music program library according to the method, so as to obtain music programs matched with the current emotion of the user by screening, and taking the music programs as recommended programs.
That is, the step S200 specifically includes the following steps:
step S210, determining the current emotion of the user according to the result of the dynamic capture analysis;
step S220, detecting the type of the current application program, and searching the local program library or the network program library according to the type;
step S230, matching the current emotion with programs in the local program library, or matching the current emotion with programs in the network program library;
step S240, setting the matched program as the recommended program.
In this embodiment, when the matched program is set as the recommended program, the programs may be sorted according to the degree of identity of the matched television program or music program, that is, the matched programs may be sorted according to the degree of similarity of the matching, so that the sorted programs are set as the recommended program.
Namely, the step S240 specifically includes the following steps:
step S241, sorting the matched programs according to the matched similarity;
step S242, setting the sorted programs as the recommended programs.
In this embodiment, screening and pairing are performed according to the emotion analysis result and the program type, so that the television program or the music program obtained through pairing is used as a recommended program and is pushed to a homepage recommendation interface of the application program, and if the matched television program or music program has a ranking state, the matched television program or music program is set as a sequence program according to the ranking, so that the user can conveniently select a desired television program from the ranked recommended program.
As shown in fig. 1, in an implementation manner of this embodiment, the program recommendation method based on human face emotion further includes the following steps:
and step S300, recommending the recommended program to the user through a push message, and carrying out set-top display on the recommended program in an application interface.
In this embodiment, after the matched program is set as the recommended program, the terminal may push the recommended program to the user through the push message and the application interface, so that the user can conveniently play the recommended program.
Specifically, when the push message is used for pushing, the terminal sends the recommended program to the associated account of the user through the push message, when the push message is sent, the push message can be sent to a message board of the application program, and when the message board is opened by the user, the recommended message in the message board can be clicked, so that the recommended program is selected from the recommended message, and the recommended message is played in time.
When the application interface is used for pushing, opening up a display area for displaying the recommended program in the application interface of the application program, for example, setting the display area on the top of the application interface; then, the recommended program is displayed in the display area, that is, the recommended program is displayed in the program display area of the application interface, and the recommended program is displayed on top, so that the user can view the recommended program at the top of the application interface, and the user can view the recommended program in time conveniently and attract the attention of the user.
Namely, the step S300 specifically includes the following steps:
step S310, sending the recommended program to an associated account of the user through the push message;
step S320, displaying the recommended program in a program display area of the application interface, and performing set-top display on the recommended program.
In this embodiment, after recommending the recommended program to the user, the terminal may further query programs that have been watched and are not matched with the current emotion, and mask or post-display the non-matched programs; the purpose of masking or post-displaying the unmatched programs is to avoid the unmatched television or music programs, thereby preventing the user from selecting such television or music programs to avoid further exciting the current mood of the user.
Namely, after the step S300, the following steps are further included:
step S400, the watched programs which are not matched with the current emotion are inquired, and the programs which are not matched are shielded or displayed after the programs are searched.
The following describes the recommendation method of the tv program and the music program in this embodiment by using specific embodiments:
as shown in fig. 2, when a television program is taken as the recommended program, the method mainly includes the following steps:
step S11, the camera shoots the human face;
step S12, performing emotion analysis on the human face through human face recognition;
step S13, the human face emotion and the television program are screened and paired;
and step S14, carrying out set-top recommendation on the screened television programs.
When a television program is taken as the recommended program, shooting a human face through a camera, performing motion capture analysis on the parts such as the eyebrows, the eyelids, the facial muscles, the mouth shapes and the like, analyzing whether a viewer is in the emotion of excitement, sadness, depression, flat and the like at the moment, screening and pairing the result of emotion analysis and the program types, pushing the result to a homepage recommending interface, performing ordered arrangement recommendation when the program is in an ordered state, and performing no recommendation or after arrangement on the programs watched in a short time; for example: when the viewer is in an excited state, love, suspicion and the like are properly recommended, when the viewer is in a sad state, comedy, synthesis and the like are recommended, when the viewer is in a depressed state, heroic steins, swordsmen, comedy and the like can be recommended, and when the viewer is in a flat state, sports, popular dramas and the like can be recommended.
As shown in fig. 3, when a music program is used as the recommended program, the method mainly includes the following steps:
step S21, the camera shoots the human face;
step S22, performing emotion analysis on the human face through human face recognition;
step S23, the human face emotion and the music program are screened and paired;
and step S24, the filtered music programs are recommended to set the top.
When a music program is taken as the recommended program, shooting a human face through a camera, performing motion capture analysis on the parts such as the eyebrows, the eyelens, the facial muscles, the mouth shapes and the like, analyzing whether a viewer is under the emotions such as excitement, sadness, depression, flat and the like at the moment, screening and pairing the emotion analysis result and the music types, pushing the emotion analysis result and the music types to a homepage recommendation interface, and performing ordered arrangement recommendation when the viewer is in an ordering state; for example, when the viewer is excited, restful light music or the like is appropriately recommended, when the viewer is sad, happy music or the like is recommended, when the viewer is depressed, generous music or the like is recommended, and when the viewer is flat, new songs, popular songs or the like is recommended.
In the embodiment, the face emotion of the user is identified through the camera, and the adaptive television program or music program is matched according to the current emotion of the user, so that the appropriate television program or music program is recommended to the user, the current emotion of the user is adjusted, and further stimulation of the emotion of the user is avoided.
Example two
As shown in fig. 4, the present embodiment provides a terminal, which includes a processor 10, and a memory 20 connected to the processor 10, where the memory 20 stores a program recommendation program based on facial emotion, and the program recommendation program based on facial emotion is used for implementing the operation of the program recommendation method based on facial emotion according to the first embodiment when executed by the processor 10; as described above.
EXAMPLE III
The present embodiment provides a storage medium, where the storage medium stores a program recommendation program based on facial emotion, and the program recommendation program based on facial emotion is used to implement the operations of the program recommendation method based on facial emotion according to the first embodiment when being executed by a processor; as described above.
In summary, the invention identifies the face emotion of the user through the camera, and matches the adaptive television program or music program according to the current emotion of the user, so as to recommend the appropriate television program or music program to the user, adjust the current emotion of the user, and avoid further activation of the emotion of the user.
Of course, it will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by a computer program instructing relevant hardware (such as a processor, a controller, etc.), and the program may be stored in a computer readable storage medium, and when executed, the program may include the processes of the above method embodiments. The storage medium may be a memory, a magnetic disk, an optical disk, etc.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.
Claims (10)
1. A program recommendation method based on face emotion is characterized by comprising the following steps:
acquiring facial expressions of a user through a camera, and carrying out facial emotion analysis on the facial expressions;
determining the current emotion of the user according to the analysis result, and matching the corresponding recommended program from a local program library or a network program library of the current application program;
recommending the recommended program to the user through a push message, and carrying out top setting display on the recommended program in an application interface.
2. The facial emotion-based program recommendation method of claim 1, wherein the facial expression of the user is obtained through a camera, and facial emotion analysis is performed on the facial expression, and the method further comprises the following steps:
and setting the local program library in the current application program in advance.
3. The program recommendation method based on facial emotion according to claim 1, wherein the facial expression of the user is obtained by a camera, and facial emotion analysis is performed on the facial expression, specifically comprising the following steps:
when the current application program is started, the position of the face is obtained through the camera;
and dynamically capturing and analyzing the eyebrow, the catch, the facial muscles and the mouth shape according to the position of the face.
4. The program recommendation method based on human face emotion according to claim 3, wherein the current emotion of the user is determined according to the analysis result, and the corresponding recommended program is matched from a local program library or a network program library of the current application program, specifically comprising the following steps:
determining a current mood of the user according to a result of the dynamic capture analysis;
detecting the type of the current application program, and searching the local program library or the network program library according to the type;
matching the current emotion with programs in the local program library, or matching the current emotion with programs in the network program library;
and setting the matched program as the recommended program.
5. The program recommendation method based on human face emotion according to claim 4, wherein the step of setting the matched program as the recommended program specifically comprises the steps of:
sorting the matched programs according to the matched similarity;
and setting the sequenced programs as the recommended programs.
6. The program recommending method based on human face emotion according to claim 1, wherein the recommending program is recommended to the user by a push message, and the recommended program is displayed on top in an application interface, specifically comprising the following steps:
sending the recommended program to an associated account of the user through the push message;
and displaying the recommended program in a program display area of the application interface, and carrying out set-top display on the recommended program.
7. The facial emotion-based program recommendation method as claimed in claim 1, wherein said recommending program is recommended to said user by push message, and said recommended program is displayed on top of an application interface, and thereafter further comprising:
and inquiring programs which are watched and not matched with the current emotion, and shielding or displaying the programs which are not matched.
8. The method of claim 1, wherein the current application program comprises a television application and a music application, and the recommended program comprises a television program and a music program.
9. A terminal comprising a processor, and a memory coupled to the processor, the memory storing a facial emotion-based program recommendation program, the facial emotion-based program recommendation program when executed by the processor being operative to implement the operations of the facial emotion-based program recommendation method as recited in any of claims 1-8.
10. A storage medium storing a facial emotion-based program recommendation program, which when executed by a processor is configured to implement the operations of the facial emotion-based program recommendation method according to any one of claims 1 to 8.
Priority Applications (1)
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