CN111291626A - Recipe recommendation method, device and system - Google Patents
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- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
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Abstract
The disclosure discloses a recipe recommendation method, device and system, and relates to the field of data recommendation. The method comprises the following steps: acquiring image information of a user; determining age information of the user based on the image information of the user; and recommending the recipe data matched with the age information to the user according to the age information of the user. The accuracy of recipe data recommendation is improved.
Description
Technical Field
The present disclosure relates to the field of data recommendation, and in particular, to a recipe recommendation method, apparatus, and system.
Background
The attention degree of people to the health condition is more and more obvious, but the health of people is influenced by inevitable external factors, and the body of people tends to be healthful through the opsonic nutrition collocation, so that the reasonable recommendation of the recipe data suitable for the people to the user is more important, but in the related technology, the recommendation precision of the recipe data is lower.
Disclosure of Invention
The invention provides a recipe recommendation method, device and system, which can solve the problem of low recipe data recommendation precision.
According to an aspect of the present disclosure, a recipe recommendation method is provided, including: acquiring image information of a user; determining age information of the user based on the image information of the user; and recommending the recipe data matched with the age information to the user according to the age information of the user.
In some embodiments, determining age information of the user based on the image information of the user comprises: determining face information and height information of the user based on the image information of the user; and determining the age information of the user according to the face information and the height information of the user.
In some embodiments, determining age information of the user based on the image information of the user comprises: determining face information, height information and first posture information of the user based on the image information of the user; based on the face information, the height information, and the first posture information of the user, age information of the user is determined.
In some embodiments, second volumetric information of the user is determined based on the image information of the user; judging whether the second body state information of the user is matched with the age information of the user; if not, the recipe data that matches the age information and has the improved second body attributes is recommended to the user.
In some embodiments, in response to the user selecting the recommended recipe data, after a predetermined time, determining whether the second modality of the user improves; if the second modality of the user is improved, the recipe data is saved.
According to another aspect of the present disclosure, there is also provided a recipe recommendation apparatus comprising: an image acquisition unit configured to acquire image information of a user; an age identifying unit configured to determine age information of the user based on the image information of the user; and a recipe recommending unit configured to recommend recipe data matching the age information to the user according to the age information of the user.
In some embodiments, the age identifying unit comprises: a face recognition module configured to determine face information of a user based on image information of the user; a height identification module configured to determine height information of the user based on the image information of the user; an age identification module configured to determine age information of the user based on the face information and the height information of the user.
In some embodiments, the age identifying unit comprises: a face recognition module configured to determine face information of a user based on image information of the user; a height identification module configured to determine height information of the user based on the image information of the user; a first body state identification module configured to determine first body state information of a user based on image information of the user; an age identification module configured to determine age information of the user based on the face information, the height information, and the first posture information of the user.
In some embodiments, the recipe recommendation unit comprises: a second volume status recognition module configured to determine second volume status information of the user based on the image information of the user; a body state judgment module configured to judge whether the second body state information of the user matches with the age information of the user; and a recipe recommending module configured to recommend recipe data that matches the age information and has an improved second body attribute to the user if the second body information of the user does not match the age information of the user.
According to another aspect of the present disclosure, there is also provided a recipe recommendation apparatus comprising: a memory; and a processor coupled to the memory, the processor configured to perform the recipe recommendation method as described above based on the instructions stored in the memory.
According to another aspect of the present disclosure, there is also provided a recipe recommendation system, comprising: an image sensor configured to acquire image information of a user; and the recipe recommending device.
In some embodiments, the display device is configured to display the recipe data recommended by the recipe recommendation apparatus.
According to another aspect of the present disclosure, a computer-readable storage medium is also proposed, on which computer program instructions are stored, which instructions, when executed by a processor, implement the recipe recommendation method described above.
In the embodiment of the disclosure, the user age is identified through the user image, and then the proper recipe data is recommended to the user according to the user age, so that the accuracy of recipe data recommendation is improved, and the actual diet requirements of the user are met.
Other features of the present disclosure and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.
The present disclosure may be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:
fig. 1 is a flow diagram of some embodiments of a recipe recommendation method of the present disclosure.
Fig. 2 is a flow diagram of further embodiments of a recipe recommendation method of the present disclosure.
Fig. 3 is a flow diagram of further embodiments of a recipe recommendation method of the present disclosure.
Fig. 4 is a schematic structural diagram of some embodiments of a recipe recommendation device of the present disclosure.
Fig. 5 is a schematic structural diagram of other embodiments of the recipe recommendation device of the present disclosure.
Fig. 6 is a schematic structural diagram of another embodiment of the recipe recommendation device of the present disclosure.
Fig. 7 is a schematic structural diagram of other embodiments of the recipe recommendation device of the present disclosure.
Fig. 8 is a schematic structural diagram of another embodiment of the recipe recommendation device of the present disclosure.
Fig. 9 is a schematic structural diagram of other embodiments of the recipe recommendation device of the present disclosure.
Fig. 10 is a schematic diagram of a structure of some embodiments of a recipe recommendation system of the present disclosure.
Detailed Description
Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.
Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
For the purpose of promoting a better understanding of the objects, aspects and advantages of the present disclosure, reference is made to the following detailed description taken in conjunction with the accompanying drawings.
Fig. 1 is a flow diagram of some embodiments of a recipe recommendation method of the present disclosure.
At step 110, image information of the user is acquired.
At step 120, age information of the user is determined based on the image information of the user.
In some embodiments, face information and height information of the user are determined based on the image information of the user, and age information of the user is determined from the face information and the height information of the user.
For example, the face of the user to be recognized is recognized, the face of the user is obtained, the face size of the user is determined, and the rough age bracket of the user is determined according to the face size of the user. For example, the face of a child is small and the face of an adult is large, and therefore, it can be roughly determined whether the user is a child or an adult. Further, the height of the user is analyzed, for example, for children, the height of children of different ages is within a predetermined range, and thus, it is possible to identify what age group the user is.
For another example, the user to be identified is subjected to face identification and height identification, and the age bracket of the user is determined according to the proportion of the face size and the height of the user. For example, the child's face size to height ratio is generally greater than the adult's face size to height ratio.
In still other embodiments, the age of the user may also be determined based on facial features of the user, such as skin texture, etc., and the identified age may then be verified in conjunction with the height information.
In step 130, recipe data matching the age information is recommended to the user based on the age information of the user.
The eating habits of all age groups are different, the tastes of food are also different, and the recipes matched with the ages of the users are recommended to the users according to the corresponding relation between the age groups and the recipe data.
For example, a diet promoting physical growth is recommended to children and adolescents, a diet balancing nutrition is recommended to users 18 to 30 years old, an anxiolytic diet is recommended to users 30 to 40 years old, and a diet resisting oxidation, increasing bone density, etc. is recommended to users after 50 years old.
In the embodiment, the user age is identified through the user image, and then the proper recipe data is recommended to the user according to the user age, so that the recipe data recommendation accuracy is improved, and the actual diet requirements of the user are met.
Fig. 2 is a flow diagram of further embodiments of a recipe recommendation method of the present disclosure.
At step 210, image information of a user is acquired.
At step 220, based on the image information of the user, face information, height information, and first posture information of the user are determined. Wherein the first volume information reflects the age of the user, such as the curvature of spine, the size of the food in body, and the like.
At step 230, age information of the user is determined based on the face information, height information, and first posture information of the user.
In some embodiments, the age of the user is determined roughly based on the face information and height information of the user, e.g., the user is determined to be an adult, and then the user is determined to be young, middle-aged, or elderly based on the first posture information of the user. For example, young people are more erect in morphology, middle-aged people are more abundant in morphology, and old people are more rickets in morphology, and thus, the age group of the user can be further determined according to the morphology.
In step 240, recipe data matching the age information is recommended to the user based on the age information of the user.
In the embodiment, the age identification is more accurate according to the face information, the height information and the first posture information of the user, and then the proper recipe data is recommended to the user according to the age of the user, so that the recommendation accuracy of the recipe data is improved.
Fig. 3 is a flow diagram of further embodiments of a recipe recommendation method of the present disclosure.
At step 310, image information of a user is acquired.
At step 320, facial information, height information, first body state information, and second body state information of the user are determined based on the image information of the user.
The second volume status information is information reflecting the health status of the user. For example, the body shape information includes position information, thickness information, waist-abdomen ratio information, and the like of the legs, waist, neck, and arms of the user.
At step 330, the age bracket of the user is determined at a coarse granularity based on the face information and height information of the user.
In step 340, the age bracket of the user is determined in fine granularity according to the first body state information of the user.
In step 350, it is determined whether the second body status information of the user matches the age information of the user, if yes, step 360 is performed, otherwise, step 370 is performed. For example, different age groups correspond to different normal posture data, if the age group to which the user belongs is identified, the normal posture data of the age group is searched, whether the posture data detected by the user is matched with the normal posture data or not is further judged, if the posture data detected by the user is matched with the normal posture data, the body of the user is healthier, and if the posture data detected by the user is not matched with the normal posture data, the health problem of the user is solved.
At step 360, the user is recommended the recipe data that matches the age bracket.
At step 370, the user is recommended the recipe data that matches the age bracket and has improved second body attributes.
In some embodiments, meat products are mainly used throughout the year and belong to users with fat-prone physique, the body types can be changed easily in a short time under the condition of high-fat energy intake, and at the moment, the recipe data with high fiber content and body slimming effect is recommended to the users, so that the users are helped to recuperate through reasonable and healthy diet, the health degree of the users is improved, and diseases such as excessive obesity are reduced.
In other embodiments, the recipe recommendation method further comprises the following steps 380 and 390.
In step 380, in response to the user selecting the recommended recipe data, after a predetermined time, it is determined whether the second body state of the user improves, and if so, step 390 is performed. Otherwise, execution continues with step 370.
In some embodiments, the user may select according to the pushed multiple health-regulation recipes, select one recipe from the multiple recipes, list the food materials for the user after confirming the recipe, the user may eat for a period of time according to the recommended health-regulation recipe, record the eating time of the user, and perform a posture analysis on the user after a period of time.
At step 390, the recipe data is saved. For example, the recipes which are successfully recommended are collected by a background server and are periodically shared to the platform for other users to select.
In the embodiment, the age bracket of the user is intelligently identified by detecting the face, the height, the posture and the like of the user, the posture of the user is further considered, namely the user is considered not only based on the age bracket but also for the body health of the user, and a nutritional and conditioning recipe is recommended for the user, so that the actual diet requirements of the user can be met, and the user experience is improved.
Fig. 4 is a schematic structural diagram of some embodiments of a recipe recommendation device of the present disclosure. The apparatus includes an image acquisition unit 410, an age identification unit 420, and a recipe recommendation unit 430.
The image acquisition unit 410 is configured to acquire image information of a user.
The age identifying unit 420 is configured to determine age information of the user based on the image information of the user.
In some embodiments, as shown in fig. 5, the age identification unit 420 includes a face identification module 421, a height identification module 422, and an age identification module 423.
The face recognition module 421 is configured to determine face information of the user based on the image information of the user; the height identification module 422 is configured to determine height information of the user based on the image information of the user; the age identification module 423 is configured to determine age information of the user based on the face information and the height information of the user.
In some embodiments, as shown in fig. 6, the age identification unit 420 includes a face identification module 421, a height identification module 422, a first posture identification module 424, and an age identification module 423.
The face recognition module 421 is configured to determine face information of the user based on the image information of the user; the height identification module 422 is configured to determine height information of the user based on the image information of the user; the first body state identification module 424 is configured to determine first body state information of the user based on the image information of the user; the age identification module 423 is configured to determine age information of the user based on the face information, the height information, and the first posture information of the user. Wherein the first volume information reflects the age of the user, such as the curvature of spine, the degree of food, and the like.
The recipe recommending unit 430 is configured to recommend recipe data matching the age information to the user according to the age information of the user.
The eating habits of all age groups are different, the tastes of food are also different, and the recipes matched with the ages of the users are recommended to the users according to the corresponding relation between the age groups and the recipe data.
In some embodiments, as shown in fig. 7, the recipe recommendation unit 430 includes a second body state identification module 431, a body state judgment module 432, and a recipe recommendation module 433.
The second volume status recognition module 431 is configured to determine second volume status information of the user based on the image information of the user; the body state judgment module 432 is configured to judge whether the second body state information of the user matches with the age information of the user; the recipe recommendation module 433 is configured to recommend to the user recipe data that matches the age information and has an improved second body attribute if the second body information of the user does not match the age information of the user.
In the embodiment, the user age is identified through the user image, and then the proper recipe data is recommended to the user according to the user age, so that the recipe data recommendation accuracy is improved, and the actual diet requirements of the user are met.
In other embodiments, the recipe recommendation unit may further include a recipe data storage unit 434. The posture determination module 432 is further configured to determine whether the second posture of the user improves after a predetermined time in response to the user selecting the recommended recipe data; the recipe data storage unit 434 saves the recipe data if the second body state of the user is improved.
Fig. 8 is a schematic structural diagram of another embodiment of the recipe recommendation device of the present disclosure. The apparatus includes a memory 810 and a processor 820. Wherein: the memory 810 may be a magnetic disk, flash memory, or any other non-volatile storage medium. The memory is used to store instructions in the embodiments corresponding to fig. 1-3. Processor 820 is coupled to memory 810 and may be implemented as one or more integrated circuits, such as a microprocessor or microcontroller. The processor 820 is configured to execute instructions stored in the memory.
In some embodiments, as also shown in fig. 9, the apparatus 900 includes a memory 910 and a processor 920. Processor 920 is coupled to memory 910 by a BUS 930. The device 900 may also be coupled to an external storage device 950 via a storage interface 940 for retrieving external data, and may also be coupled to a network or another computer system (not shown) via a network interface 960. And will not be described in detail herein.
In the embodiment, the data instructions are stored in the memory and processed by the processor, so that the accuracy of the recipe data recommendation is improved.
Fig. 10 is a schematic diagram of a structure of some embodiments of a recipe recommendation system of the present disclosure. The system comprises an image sensor 1010 and a recipe recommending means 1020, the recipe recommending means 1020 being described in detail in the above embodiments and not further described here.
The image sensor 1010 is configured to capture image information of a user. Such as a camera on a cell phone.
In other embodiments, the system may further include a display device 1030 configured to display the recipe data recommended by the recipe recommending apparatus 1020. The display device 1030 may be a display screen on a cell phone.
In other embodiments, a computer-readable storage medium has stored thereon computer program instructions which, when executed by a processor, implement the steps of the method in the embodiments corresponding to fig. 1-3. As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, apparatus, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Thus far, the present disclosure has been described in detail. Some details that are well known in the art have not been described in order to avoid obscuring the concepts of the present disclosure. It will be fully apparent to those skilled in the art from the foregoing description how to practice the presently disclosed embodiments.
Although some specific embodiments of the present disclosure have been described in detail by way of example, it should be understood by those skilled in the art that the foregoing examples are for purposes of illustration only and are not intended to limit the scope of the present disclosure. It will be appreciated by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.
Claims (13)
1. A recipe recommendation method comprising:
acquiring image information of a user;
determining age information of the user based on the image information of the user;
and recommending the recipe data matched with the age information to the user according to the age information of the user.
2. The recipe recommendation method of claim 1, wherein determining age information of the user based on the image information of the user comprises:
determining face information and height information of the user based on the image information of the user;
and determining the age information of the user according to the face information and the height information of the user.
3. The recipe recommendation method of claim 1, wherein determining age information of the user based on the image information of the user comprises:
determining face information, height information and first posture information of the user based on the image information of the user;
determining age information of the user based on the face information, the height information, and the first posture information of the user.
4. The recipe recommendation method according to any one of claims 1 to 3, further comprising:
determining second body state information of the user based on the image information of the user;
judging whether the second body state information of the user is matched with the age information of the user;
and if not, recommending the recipe data which is matched with the age information and has the improved second body state attribute to the user.
5. The recipe recommendation method of claim 4, further comprising:
determining, after a predetermined time, whether a second modality of the user improves in response to the user selecting recommended recipe data;
if the second modality of the user is improved, the recipe data is saved.
6. A recipe recommendation apparatus comprising:
an image acquisition unit configured to acquire image information of a user;
an age identifying unit configured to determine age information of the user based on image information of the user;
and the recipe recommending unit is configured to recommend recipe data matched with the age information to the user according to the age information of the user.
7. The recipe recommendation device according to claim 6, wherein the age identification unit comprises:
a face recognition module configured to determine face information of the user based on image information of the user;
a height identification module configured to determine height information of the user based on the image information of the user;
an age identification module configured to determine age information of the user based on the face information and the height information of the user.
8. The recipe recommendation device according to claim 6, wherein the age identification unit comprises:
a face recognition module configured to determine face information of the user based on image information of the user;
a height identification module configured to determine height information of the user based on the image information of the user;
a first body state identification module configured to determine first body state information of the user based on image information of the user;
an age identification module configured to determine age information of the user based on the face information, height information, and first posture information of the user.
9. The recipe recommendation device according to any one of claims 6 to 8, wherein the recipe recommendation unit includes:
a second volume status recognition module configured to determine second volume status information of the user based on the image information of the user;
a posture determination module configured to determine whether second posture information of the user matches age information of the user;
a recipe recommendation module configured to recommend recipe data that matches age information and has improved second body attributes to the user if the second body information of the user does not match the age information of the user.
10. A recipe recommendation apparatus comprising:
a memory; and
a processor coupled to the memory, the processor configured to perform the recipe recommendation method of any of claims 1-5 based on instructions stored in the memory.
11. A recipe recommendation system comprising:
an image sensor configured to acquire image information of a user; and
the recipe recommendation device of any one of claims 6 to 10.
12. The recipe recommendation system of claim 11, further comprising:
a display device configured to display the recipe data recommended by the recipe recommending apparatus.
13. A computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the recipe recommendation method of any one of claims 1 to 5.
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| CN202010048556.3A CN111291626A (en) | 2020-01-16 | 2020-01-16 | Recipe recommendation method, device and system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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