CN114417189A

Movatterモバイル変換

Info

Publication number: CN114417189A
Application number: CN202111682564.4A
Authority: CN
Inventors: 冯可
Original assignee: Yankan Technology Shenzhen Co ltd
Current assignee: Yankan Technology Shenzhen Co ltd
Priority date: 2021-12-31
Filing date: 2021-12-31
Publication date: 2022-04-29

Abstract

The application relates to an intelligent recommendation method, a cabinet body, an electronic device and a medium based on face recognition, wherein the method comprises the following steps: identifying user face information and acquiring user information corresponding to the user face information; matching schedule data corresponding to the user information, and acquiring recommended clothes based on the schedule data; and determining a storage position corresponding to the recommended clothes, and prompting the storage position. The clothes recommendation method has the advantages that the clothes recommendation is carried out on the user by acquiring the schedule data corresponding to the user, so that the proper clothes can be accurately provided for the user, the problem that the user cannot decide between the clothes is avoided, meanwhile, the proper clothes can be searched for according to different weather, the clothes are comfortable and attractive to wear, and the user experience is improved.

Description

Intelligent recommendation method based on face recognition, cabinet, electronic device and medium

Technical Field

The application relates to the field of home management, in particular to an intelligent recommendation method based on face recognition, a cabinet body, an electronic device and a medium.

Background

The existing wardrobe only has a storage function, and a user puts clothes into the wardrobe after finishing the clothes; however, when the number of the clothes is too large, the user often has a case that the user can not choose among a plurality of clothes, and the user often has a case that the user does not know what kind of clothes is suitable for keeping warm due to weather change.

Disclosure of Invention

The application provides an intelligent recommendation method, a cabinet body, an electronic device and a medium based on face recognition, and aims to solve the technical problem that a user is difficult to decide among numerous clothes in the prior art.

In order to solve the above technical problem or at least partially solve the above technical problem, the present application provides an intelligent recommendation method based on face recognition, including the steps of:

identifying user face information and acquiring user information corresponding to the user face information;

matching schedule data corresponding to the user information, and acquiring recommended clothes based on the schedule data;

and determining a storage position corresponding to the recommended clothes, and prompting the storage position.

Optionally, the step of obtaining recommended clothes based on the schedule data includes:

obtaining travel information in the schedule data and clothes characteristics of clothes stored in a cabinet body, wherein the travel information comprises first weather data of a target place, the number of the target places is at least one, the clothes characteristics comprise a cooling and heating grade, and the cooling and heating grade is generated based on habit data corresponding to the user information;

determining a first cooling and heating level corresponding to the first day air data;

taking the stored clothes with the cooling and heating level consistent with the first cooling and heating level as first alternative clothes;

and acquiring the recommended clothes based on the first candidate clothes and the schedule data.

Optionally, the travel information includes scene information; the step of obtaining the recommended clothing based on the first candidate clothing and the schedule data includes:

acquiring clothing characteristics of the first alternative clothing, wherein the clothing characteristics comprise occasion labels;

and taking the first candidate clothes with the occasion labels corresponding to the scene information as the recommended clothes.

acquiring a current date, and judging whether schedule data corresponding to the current date exist or not;

if the schedule data corresponding to the current date does not exist, acquiring habit data corresponding to the user information, and acquiring the recommended clothes based on the habit data;

and if the schedule data corresponding to the current date exist, acquiring recommended clothes based on the schedule data.

Optionally, the step of obtaining the recommended clothing based on the habit data includes:

acquiring second weather data corresponding to the current position and clothes characteristics of clothes stored in a cabinet body, wherein the clothes characteristics comprise cooling and heating levels, and the cooling and heating levels are generated based on habit data corresponding to the user information;

determining a second cold and warm grade corresponding to the second weather data;

taking the stored clothes with the cooling and heating level consistent with the second cooling and heating level as second alternative clothes;

acquiring the recommended clothing based on the second alternative clothing and the habit data.

matching first habit data corresponding to the current date in the habit data;

and acquiring the recommended clothes according to the first habit data.

obtaining makeup features corresponding to the face information of the user;

matching second habit data corresponding to the makeup features in the habit data;

and acquiring the recommended clothes according to the second habit data.

In order to achieve the above object, the present invention also provides a cabinet, including:

the first identification module is used for identifying the face information of the user and acquiring the user information corresponding to the face information of the user;

the first matching module is used for matching schedule data corresponding to the user information and acquiring recommended clothes based on the schedule data;

and the first determining module is used for determining the storage position corresponding to the recommended clothes and carrying out prompt operation on the storage position.

Optionally, the first matching module comprises:

the first obtaining unit is used for obtaining travel information in the schedule data and clothes characteristics of clothes stored in the cabinet body, wherein the travel information comprises first weather data of target places, the number of the target places is at least one, the clothes characteristics comprise a cooling and heating grade, and the cooling and heating grade is generated based on habit data corresponding to the user information;

the first determining unit is used for determining a first cooling and heating level corresponding to the first antenna data;

the first execution unit is used for taking the stored clothes with the cooling and heating level consistent with the first cooling and heating level as first alternative clothes;

a first obtaining unit, configured to obtain the recommended clothing based on the first candidate clothing and the schedule data.

Optionally, the travel information includes scene information; the first acquisition unit includes:

a first obtaining subunit, configured to obtain a clothing feature of the first candidate clothing, where the clothing feature includes an occasion label;

and the first execution subunit is used for taking the first candidate clothes of which the occasion labels correspond to the scene information as the recommended clothes.

Optionally, the first matching module comprises:

the first judging unit is used for acquiring the current date and judging whether schedule data corresponding to the current date exist or not;

a second obtaining unit, configured to obtain habit data corresponding to the user information if there is no schedule data corresponding to the current date, and obtain the recommended clothing based on the habit data;

and the second execution unit is used for acquiring recommended clothes based on the schedule data if the schedule data corresponding to the current date exists.

Optionally, the second obtaining unit includes:

the second acquiring subunit is used for acquiring second weather data corresponding to the current position and clothes characteristics of clothes stored in the cabinet body, wherein the clothes characteristics comprise cooling and heating levels, and the cooling and heating levels are generated based on habit data corresponding to the user information;

the first determining subunit is used for determining a second cold and warm level corresponding to the second weather data;

the second execution subunit is used for taking the stored clothes with the cooling and heating level consistent with the second cooling and heating level as second alternative clothes;

a third obtaining subunit, configured to obtain the recommended clothing item based on the second clothing item candidate and the habit data.

Optionally, the second obtaining unit includes:

the first matching subunit is used for matching first habit data corresponding to the current date in the habit data;

and the third acquisition subunit is used for acquiring the recommended clothes according to the first habit data.

Optionally, the second obtaining unit includes:

the fourth acquisition subunit is used for acquiring the makeup features corresponding to the face information of the user;

a second matching subunit for matching second habit data corresponding to the makeup feature in the habit data;

and the fifth acquiring subunit is used for acquiring the recommended clothes according to the second habit data.

To achieve the above object, the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the intelligent recommendation method based on face recognition as described above.

To achieve the above object, the present invention further provides a computer-readable storage medium, having a computer program stored thereon, where the computer program is executed by a processor to implement the steps of the intelligent recommendation method based on face recognition as described above.

The invention provides an intelligent recommendation method, a cabinet body, an electronic device and a medium based on face recognition, which are used for recognizing face information of a user and acquiring user information corresponding to the face information of the user; matching schedule data corresponding to the user information, and acquiring recommended clothes based on the schedule data; and determining a storage position corresponding to the recommended clothes, and prompting the storage position. The clothes recommendation method has the advantages that the clothes recommendation is carried out on the user by acquiring the schedule data corresponding to the user, so that the proper clothes can be accurately provided for the user, the problem that the user cannot decide between the clothes is avoided, meanwhile, the proper clothes can be searched for according to different weather, the clothes are comfortable and attractive to wear, and the user experience is improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.

FIG. 1 is a schematic flow chart of a first embodiment of an intelligent recommendation method based on face recognition according to the present invention;

FIG. 2 is a detailed flowchart of step S20 of the intelligent recommendation method based on face recognition according to the second embodiment of the present invention;

fig. 3 is a schematic block diagram of an electronic device according to the present invention.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The invention provides an intelligent recommendation method based on face recognition, and referring to fig. 1, fig. 1 is a flow diagram of a first embodiment of the intelligent recommendation method based on face recognition, and the method comprises the following steps:

step S10, identifying the user face information and acquiring the user information corresponding to the user face information;

in the embodiment, the image acquisition equipment can be arranged to acquire the face information of the user; the image acquisition device in this embodiment is a camera. In order to avoid revealing the privacy of the user, the camera can be further set to be an infrared camera or a TOF camera and the like. The operation of recognizing the face information of the user can be set according to the actual application scene and the need, and is not limited herein. The identity of the user can be obtained by identifying the facial information of the user; it should be noted that different users correspond to different user information. Specifically, a corresponding user account may be generated for each user, and the user account is recorded with the user-related data, so as to generate the user information according to the related data.

Step S20, matching schedule data corresponding to the user information and obtaining recommended clothes based on the schedule data;

the schedule data is a schedule plan set by a user; specifically, the cabinet body can be bound with daily application accounts such as a mailbox account, a calendar account and the like of the user, and the schedule plan is adjusted in real time according to the setting of the user in the daily application; the user can also set the schedule plan directly on the control terminal of the cabinet body.

Step S30, determining a storage location corresponding to the recommended clothing item, and performing a presentation operation on the storage location.

The storage position can be set according to the actual cabinet structure, for example, a closed storage space is used as a storage position; the separated areas are used as one storage position, or the cabinet body is divided into different storage positions according to functions, and the storage positions are not limited in the description. The storage positions of different articles can be set according to different conditions, after the articles are placed in the cabinet body, the information of the articles is associated with the placed storage positions, and the storage positions of the articles can be determined through the target information.

The embodiment recommends the clothing for the user through acquireing the schedule data that corresponds with the user for can accurately provide suitable clothing for the user, avoid the user to decide for a decision between the clothing, simultaneously, can look for suitable clothing to different weather, make the dress comfortable and good-looking, promote user experience.

Further, referring to fig. 2, in a second embodiment of the intelligent recommendation method based on face recognition of the present invention proposed based on the first embodiment of the present invention, the step S20 includes the steps of:

step S21, obtaining travel information in the schedule data and clothes characteristics of clothes stored in a cabinet body, wherein the travel information comprises first weather data of target places, the number of the target places is at least one, the clothes characteristics comprise a cooling and heating grade, and the cooling and heating grade is generated based on habit data corresponding to the user information;

step S22, determining a first cold and warm grade corresponding to the first antenna data;

step S23, the stored clothes with the same temperature and humidity level as the first alternative clothes are used as the first alternative clothes;

step S24, obtaining the recommended clothing based on the first candidate clothing and the schedule data.

Travel information includes, but is not limited to, target location, time, travel days, and the like; when the travel information does not include the target point, the current location point may be the target point. The weather data can be obtained through networking query; weather data includes, but is not limited to, air temperature, air quality, and weather. It should be noted that the user may need different places in different channels in a single schedule, and therefore, the weather data of different target places may be obtained respectively, and corresponding recommended clothes may be obtained based on different weather data respectively.

The cold and warm grades are used for representing the warm keeping degree required by the user at different air temperatures; because different users have different sensitivity degrees to the temperature, the cooling and heating level of the most suitable user can be determined according to the habit data of the user; specifically, for example, the warm keeping degree of clothes selected by a user at different temperatures is counted, for example, at 30 ℃, the user selects short sleeves and short pants, at 20 ℃, the user selects long sleeves, at 10 ℃, the user selects thick coats, and at 0 ℃, the user selects thin down jackets; and dividing the temperature according to the warm-keeping degree of the clothes selected by the user to obtain the cold and warm grade corresponding to the user.

Clothes meeting the weather conditions are screened out through the cold and warm grades, and the follow-up matching data volume is reduced while the user needs can be met. The specific scheme of obtaining recommended clothes based on schedule data can refer to the following embodiments.

Further, in a third embodiment of the intelligent recommendation method based on face recognition provided by the second embodiment of the present invention, the travel information includes scene information; the step S24 includes the steps of:

step S241, obtaining clothes characteristics of the first candidate clothes, wherein the clothes characteristics comprise occasion labels;

step S242 is performed to set the first candidate clothes corresponding to the scenario tag and the scenario information as the recommended clothes.

The scene information is used for representing the style of the travel scene; the occasion label is used for representing the style of clothes; setting an incidence relation between the scene information and the occasion label; if the scene label is a conference, the associated clothes style can be business, serious, professional and the like; if the scene label is an amusement park, the associated clothes style can be leisure, color, refreshing and the like; the specific scene information and the occasion label may be set according to the actual application scene and the user requirement, and are not limited herein. Meanwhile, the scene information and the occasion label can be preset or updated by an operator and can also be set by a user.

By matching the scene information corresponding to the occasion label, clothes conforming to the schedule scene can be recommended for the user, and the use experience of the user is improved.

Further, in a fourth embodiment of the intelligent recommendation method based on face recognition of the present invention proposed based on the first embodiment of the present invention, the step S20 includes the steps of:

step S25, acquiring the current date and judging whether schedule data corresponding to the current date exists;

step S26, if there is no schedule data corresponding to the current date, acquiring habit data corresponding to the user information, and acquiring the recommended clothing based on the habit data;

and step S27, if the schedule data corresponding to the current date exists, acquiring recommended clothes based on the schedule data.

When schedule data exist in the current date, the fact that the user has a specific schedule is shown, so that accurate clothes recommendation can be provided for the user on the basis of the schedule of the user; when schedule data does not exist on the current date, the user is considered to have no specific schedule currently, and at the moment, clothes selection which is possibly inclined by the user needs to be judged according to habits of the user.

The habit data comprises historical dressing data of the user; it should be noted that, because weather conditions of the whole year are different, and meanwhile, too-long historical data does not have too high referential performance, data generation habit data closer to the current date can be selected from historical dressing data, and if only historical dressing data generation habit data within one month from the current date is selected, taking the current date as 5.1 as an example, historical dressing data of 4.1-5.1 in the current year or historical dressing data generation habit data of 4.1-6.1 in the past year are acquired; or selecting historical dressing data according to the current weather condition, and if the current weather condition is obtained, taking 20 ℃ as an example, obtaining data corresponding to the temperature and the current temperature within a certain deviation range in the historical dressing data, such as 18-22 ℃, to generate habit data. It should be noted that the specific habit data selection can be set according to the actual application location and the user requirement.

The embodiment can accurately recommend clothes for the user under different conditions.

The step S26 includes the steps of:

step S261, second weather data corresponding to the current position and clothes characteristics of clothes stored in the cabinet body are obtained, wherein the clothes characteristics comprise a cooling and heating level, and the cooling and heating level is generated based on habit data corresponding to the user information;

step S262, determining a second cold and warm grade corresponding to the second weather data;

step S263, the stored clothes with the cooling and heating level consistent with the second cooling and heating level are used as second alternative clothes;

step S264, obtaining the recommended clothing based on the second clothing candidate and the habit data.

In this embodiment, the first antenna data and the second cooling/heating level can be specifically set, which is not described herein.

The step S26 includes the steps of:

step 265, matching first habit data corresponding to the current date in the habit data;

and step S266, acquiring the recommended clothes according to the first habit data.

Generally, when there is no schedule, the user needs a specific style of clothes corresponding to a specific date; if the current date is the working day, the data of which the date is the working day in the habit data is acquired as first habit data; during weekends, clothes which are more leisure are needed, so that if the current date is weekend, the data with the date of weekend in the habit data is acquired as first habit data; in a similar way, different festivals, commemorative days and the like can be set specifically, and are not described herein any more. Since the number of the clothes in the first habit data may be excessive, the first habit data needs to be filtered, such as obtaining recommended clothes from the first habit data through the number of times of using the clothes, the degree of freshness, and the like.

The present embodiment recommends laundry for the user by a corresponding habit data at a specific date, so that the user's needs can be accurately judged.

The step S26 includes the steps of:

step S267, obtaining makeup features corresponding to the face information of the user;

step S268, matching second habit data corresponding to the makeup features in the habit data;

step S269, acquiring the recommended clothing according to the second habit data.

For a user who makes up, different clothes are often needed to be matched according to different makeup, so that the face information of the user can be identified to obtain the current makeup characteristics of the user; the cosmetic features may include cosmetic color systems, cosmetic styles, and the like. The specific identification mode can be selected according to actual needs, and is not described herein. The habit data can store the historical makeup characteristics of the user at the same time, and meanwhile, the historical makeup characteristics can be associated with the clothes selected by the user at the same time; after the current makeup feature is acquired, habit data corresponding to the historical makeup feature and the current makeup feature can be matched as second habit data. And then obtaining recommended clothes through the second habit data. Since the number of the clothes in the second habit data may be too large, the second habit data needs to be filtered, such as obtaining recommended clothes from the second habit data through the number of times of using the clothes, the degree of freshness, and the like.

It should be noted that, the above embodiment shows that different habit data are screened according to different conditions, and then recommended clothes are obtained according to the habit data; in actual application, the most accurate clothes recommendation can be realized by selecting or combining the different modes according to application scenes and user needs.

Further, in a further embodiment, in addition to automatically recognizing the face of the user, the user may trigger an article taking instruction to take the clothing by himself, specifically:

receiving an article taking instruction, and acquiring first target information of an article corresponding to the article taking instruction;

determining a storage position corresponding to the first target information;

and prompting the storage position corresponding to the first target information.

The fetching instruction is an instruction sent by a user and used for representing the object fetching; the fetching instruction can be sent in different modes, such as a fetching key arranged on the cabinet body, voice sending or other triggering conditions, and the fetching instruction can be sent in a mode that the user stays in front of the cabinet body for more than preset time. The specific sending mode of the fetching instruction can be set according to the actual application scenario and the need, and is not limited herein.

The fetching instruction corresponds to an article to be fetched, and the first target information is related information of the article to be fetched, including but not limited to the number, identification, type, color, usage, name, material, placing time, and the like of the article.

Further, when a user triggers a fetching instruction, options such as manual selection, intelligent recommendation and historical record can be provided, if the user selects manual selection, the user can determine an article to be fetched in modes such as voice, character input or article picture providing, and further obtain first target information corresponding to the article; if the user selects intelligent recommendation, acquiring a taking record of the user within a preset time period, and analyzing the articles required to be taken by the user according to the taking record; displaying the analyzed article for selection by a user, and further acquiring first target information corresponding to the article selected by the user; if the user selects options such as the historical record, the taking record of the user in the preset time period is obtained, the articles in the taking record are displayed for the user to select, and then the first target information corresponding to the articles selected by the user is obtained.

According to the embodiment, the storage position corresponding to the target information of the article is recorded in advance, so that when a user needs to take the article, the storage position of the article can be directly obtained, and the storage position is prompted through a prompting operation, so that the user can find the storage position intuitively; the user can take the product conveniently.

Further, the acquiring the first target information of the article corresponding to the fetching instruction comprises:

starting the image acquisition equipment, and acquiring images through the image acquisition equipment;

and identifying the collected image collected by the image collecting equipment to obtain first target information corresponding to the collected image.

The image acquisition device in this embodiment is a camera. In order to avoid revealing the privacy of the user, the camera can be further set to be an infrared camera or a TOF camera and the like.

The user can store the photos of the articles on a terminal with a display function, such as a mobile phone or a tablet in advance, and when the camera carries out image acquisition, the photos are placed in an acquisition area of the camera.

It should be noted that, when image acquisition is performed, whether an object meeting preset characteristics, such as clothes, trousers, etc., is included in an acquired image is detected in real time; when the collected image is not detected to contain the object which accords with the preset characteristics, the image collecting body is kept; and when the acquired image is detected to contain the object which accords with the preset characteristics, taking the image as the acquired image, and stopping image acquisition. Further identifying the collected image to obtain first target information; specifically, the identification mode may be set according to an actual application scenario and needs, for example, a neural network model is set, and the acquired image is identified by the neural network model, which is not limited herein.

The embodiment can reasonably determine the articles required to be taken by the user through image acquisition.

Further, the step of obtaining the first target information of the article corresponding to the fetching instruction comprises the following steps:

acquiring a storage target information table of the cabinet body, and acquiring a stored image corresponding to a currently stored article from the storage target information table;

displaying the stored image on the display device;

if a selection instruction based on the stored image is received, taking the stored image corresponding to the selection instruction as a target image;

and taking the information corresponding to the target image in the storage target information table as the first target information.

The display device is a display; a user can select the functions of the cabinet body through the display equipment, check objects stored in the cabinet body and the like; password protection can also be carried out on the cabinet body, and the display displays corresponding contents after the user display unlocks the cabinet body.

The storage target information table contains the corresponding relation between the articles stored in the cabinet and the storage positions and the related information of each article. The storage target information table is updated according to the article taken or placed each time; when the article is taken, deleting the information corresponding to the article from the storage target information table; and when the article is placed, adding information corresponding to the article into the storage target information table.

The stored images are images corresponding to the articles currently stored in the cabinet body; that is, images corresponding to the respective articles in the target information table are stored. When the stored images are displayed, classified display can be performed according to factors such as storage positions, types, colors and the like; the user can select the object image needing to be taken from the displayed images to trigger a selection instruction; the selection instruction can be triggered by remote control, touch operation, voice and the like; after receiving a selection instruction; acquiring target information of an article corresponding to the selection instruction; i.e. the first object information.

The present embodiment enables the user to conveniently select an item to be taken.

Further, the method comprises the steps of:

receiving a placement instruction, and acquiring second target information corresponding to the placement instruction;

matching a storage position corresponding to the second target information;

and prompting the storage position corresponding to the second target information.

The second target information comprises a material identifier; the matching of the storage location corresponding to the second target information comprises the steps of:

acquiring material types corresponding to the storage positions;

and taking the storage position corresponding to the material type and the material mark as the second storage position.

The placement instruction is an instruction for representing a placed article, and the sending method of the placement instruction can be set by analogy with reference to the fetching instruction, which is not described herein again.

The second target information is used to characterize the characteristics of the article to be placed, including but not limited to the article's number, identification, type, color, use, name, material, time of placement, etc.

The types of the stored articles in each storage position can be preset, and the articles can be divided into different storage positions according to different materials, use scenes, types and colors; when the articles are stored, the articles are divided into corresponding storage positions according to the characteristics of the articles.

After the storage position corresponding to the second target information is determined, prompt operation is carried out on the storage position corresponding to the second target information so that a user can know the putting position, and the article is prevented from reaching the storage position corresponding to the second target information according to the prompt operation. The prompting operation can be performed according to the above scheme for the storage location, and is not described herein again.

This embodiment can make the user place article conveniently, records the information of article simultaneously.

Further, the method comprises the steps of:

receiving a nursing instruction, and acquiring a nursing plan corresponding to the nursing instruction, wherein the nursing plan comprises nursing sub-plans set based on different storage positions;

executing the corresponding care sub-plan for each of the storage locations.

The nursing instruction comprises but is not limited to a sterilization and disinfection instruction, a humidity regulation and control instruction or a fragrance treatment instruction; the user triggers different nursing instructions by needs; when a sterilization and disinfection instruction is triggered, ultraviolet equipment arranged in the cabinet body can be controlled to perform ultraviolet disinfection; when a humidity regulation instruction is triggered, dehumidification operation can be performed through dehumidification equipment; when the fragrance processing instructions are triggered, the volatilization rate of the fragrance device can be controlled. The specific nursing operation can be set according to the actual application scenario and needs, and is not limited herein.

It should be noted that different nursing requirements are different due to different types of articles stored in different storage positions, so that different nursing sub-plans are set for different storage positions, for example, for sterilization and disinfection instructions, a longer sterilization time is set for a storage position for storing thicker clothes such as down jackets and cotton coats, and a shorter sterilization time is set for a storage position for storing thinner clothes such as short sleeves. Other care plans can be set according to the analogy, which is not described herein.

The embodiment can carry out nursing operation to the article that the cabinet body was deposited according to user's needs, has widened the application scene of the cabinet body.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.

Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present application.

The application also provides a cabinet body for implementing the intelligent recommendation method based on the face recognition, and the cabinet body comprises:

The cabinet body recommends for the user through acquireing the schedule data that corresponds with the user for can accurately provide suitable clothing for the user, avoid the user to decide for a decision between the clothing, simultaneously, can look for suitable clothing to different weather, make to wear comfortable and good-looking, promote user experience.

It should be noted that the first identifying module in this embodiment may be configured to execute step S10 in this embodiment, the first matching module in this embodiment may be configured to execute step S20 in this embodiment, and the first determining module in this embodiment may be configured to execute step S30 in this embodiment.

Further, the first matching module comprises:

Further, the travel information includes scene information; the first acquisition unit includes:

Further, the first matching module comprises:

Further, the second acquisition unit includes:

It should be noted here that the modules described above are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the disclosure of the above embodiments. It should be noted that the modules as a part of the cabinet may be implemented by software or hardware, where the hardware environment includes a network environment.

Referring to fig. 3, the electronic device may include components such as acommunication module 10, amemory 20, and aprocessor 30 in a hardware structure. In the electronic device, theprocessor 30 is connected to thememory 20 and thecommunication module 10, respectively, thememory 20 stores thereon a computer program, which is executed by theprocessor 30 at the same time, and when executed, implements the steps of the above-mentioned method embodiments.

Thecommunication module 10 may be connected to an external communication device through a network. Thecommunication module 10 may receive a request from an external communication device, and may also send a request, an instruction, and information to the external communication device, where the external communication device may be another electronic apparatus, a server, or an internet of things device, such as a television.

Thememory 20 may be used to store software programs as well as various data. Thememory 20 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function (for example, user information corresponding to the obtained user face information), and the like; the storage data area may include a database, and the storage data area may store data or information created according to use of the system, or the like. Further, thememory 20 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

Theprocessor 30, which is a control center of the electronic device, connects various parts of the entire electronic device using various interfaces and lines, and performs various functions of the electronic device and processes data by operating or executing software programs and/or modules stored in thememory 20 and calling data stored in thememory 20, thereby performing overall monitoring of the electronic device.Processor 30 may include one or more processing units; alternatively, theprocessor 30 may integrate an application processor, which primarily handles operating systems, user interfaces, applications, etc., and a modem processor, which primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into theprocessor 30.

Although not shown in fig. 3, the electronic device may further include a circuit control module, which is used for connecting with a power supply to ensure the normal operation of other components. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 3 does not constitute a limitation of the electronic device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.

The invention also proposes a computer-readable storage medium on which a computer program is stored. The computer-readable storage medium may be theMemory 20 in the electronic apparatus in fig. 3, and may also be at least one of a ROM (Read-Only Memory)/RAM (Random Access Memory), a magnetic disk, and an optical disk, and the computer-readable storage medium includes instructions for enabling a terminal device (which may be a television, an automobile, a mobile phone, a computer, a server, a terminal, or a network device) having a processor to execute the method according to the embodiments of the present invention.

In the present invention, the terms "first", "second", "third", "fourth" and "fifth" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance, and those skilled in the art can understand the specific meanings of the above terms in the present invention according to specific situations.

In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

Although the embodiment of the present invention has been shown and described, the scope of the present invention is not limited thereto, it should be understood that the above embodiment is illustrative and not to be construed as limiting the present invention, and that those skilled in the art can make changes, modifications and substitutions to the above embodiment within the scope of the present invention, and that these changes, modifications and substitutions should be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. An intelligent recommendation method based on face recognition is characterized by comprising the following steps:

2. The intelligent recommendation method based on face recognition according to claim 1, wherein the step of obtaining recommended clothes based on the schedule data comprises:

3. The intelligent recommendation method based on face recognition according to claim 2, wherein the travel information includes scene information; the step of obtaining the recommended clothing based on the first candidate clothing and the schedule data includes:

4. The intelligent recommendation method based on face recognition according to claim 1, wherein the step of obtaining recommended clothes based on the schedule data comprises:

5. The intelligent recommendation method based on face recognition according to claim 4, wherein the step of obtaining the recommended clothing based on the habit data comprises:

6. The intelligent recommendation method based on face recognition according to claim 4, wherein the step of obtaining the recommended clothing based on the habit data comprises:

matching first habit data corresponding to the current date in the habit data;

and acquiring the recommended clothes according to the first habit data.

7. The intelligent recommendation method based on face recognition according to claim 4, wherein the step of obtaining the recommended clothing based on the habit data comprises:

obtaining makeup features corresponding to the face information of the user;

and acquiring the recommended clothes according to the second habit data.

8. A cabinet, characterized in that the cabinet comprises:

9. An electronic device, characterized in that the electronic device comprises a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the intelligent face recognition based recommendation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the intelligent face recognition-based recommendation method according to any one of claims 1 to 7.