Intelligent recommendation method and system for beauty makeup products based on facial feature extraction and storage medium

Abstract

The invention discloses an intelligent recommendation method and system for beauty makeup products based on facial feature extraction and a storage medium, and relates to the field of artificial intelligence and face recognition. Acquiring a target expected makeup type of the user and facial features of the user by using the intelligent beauty makeup mirror, performing double encryption processing on the facial features of the user, and calculating the facial flatness and facial shadow distribution condition of the user; recommending facial makeup according to the calculation result and the target expected makeup type, and presenting the recommended makeup on the face of the user through the intelligent beauty makeup mirror; historical purchase records and browsing behaviors of the user are analyzed, and other users similar to the facial features of the user are found out, so that beauty makeup products are pre-selected; and calculating the similarity between the product and the facial features and the facial makeup of the user, and correspondingly recommending a beauty makeup product according to the similarity. According to the invention, the intelligent beauty makeup mirror is utilized to realize the functions, so that more personalized, accurate and convenient makeup experience can be provided for the user.

Description

Technical Field

[0001] The present invention relates to the fields of artificial intelligence and face recognition, and more specifically to an intelligent recommendation method, system and storage medium for beauty products based on facial feature extraction. Background Art

[0002] Artificial Intelligence (AI), as an indispensable driving force for new scientific and technological changes and industrial development, is increasingly used in the field of beauty. Deep Learning, as an important technology in AI, has promoted the research of artificial neural networks through the development of technologies such as multi-layer perceptron (MLP) and back propagation algorithm (BP). The concept of deep learning was proposed by Hinton et al. in 2006, and the deep belief network (DBN) model was subsequently proposed to solve the training problem of deep neural networks.

[0003] The application of deep learning in computer vision, natural language processing and other fields provides technical support for the intelligent recommendation of beauty products. Through the deep learning model, the facial area can be efficiently identified and key feature points such as eyes, nose, mouth, etc. can be extracted, laying the foundation for subsequent makeup recommendations and migration.

[0004] Recommendation algorithms are a technology that uses information such as user history, interests, and social networks to recommend personalized content or products to users. In the intelligent recommendation of beauty products, recommendation algorithms are used to generate unique makeup effects for users based on factors such as facial features, skin color, and preferences.

[0005] In summary, the deep integration of technologies in multiple fields such as artificial intelligence, deep learning, computer vision, and recommendation algorithms provides strong technical support for the intelligent recommendation of beauty products, and promotes the digitalization and intelligentization of the beauty industry. However, there are also various disadvantages. For example, the accuracy of facial feature extraction cannot be guaranteed due to the user's environment, and there is a risk of leakage of facial feature information after extraction. Therefore, how to further improve the above technical solutions and solve technical problems such as feature extraction, data security, and poor user experience still requires in-depth research by technical personnel in this field. Summary of the invention

[0006] In view of this, the present invention provides a method, system and storage medium for intelligent recommendation of beauty products based on facial feature extraction to solve any one or more problems in the background technology.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] An intelligent recommendation method for beauty products based on facial feature extraction includes the following steps:

[0009] The smart makeup mirror is used to obtain the user's target makeup type and facial features, and the user's facial features are double-encrypted. The first encryption is used for this makeup recommendation, and the second encryption is used to build a user sample database to calculate the user's facial flatness and facial shadow distribution;

[0010] Recommend facial makeup based on the calculation results and the target expected makeup type, and present the recommended makeup on the user's face through the smart beauty mirror;

[0011] The user connects to the smart beauty mirror through a mobile terminal, and transmits the user's beauty purchase information to the smart beauty mirror MCU through the mobile terminal, analyzes the user's historical purchase records and browsing behavior, finds other users with similar facial features to the user, and pre-selects beauty products;

[0012] Based on the recommended facial makeup features and beauty product attributes, the similarity between the product and the user's facial features and facial makeup is calculated, and beauty products are recommended based on the level of similarity.

[0013] Optionally, double encryption of user facial features includes:

[0014] First encryption: The facial feature data of the current user is transmitted to the blockchain using symmetric encryption to obtain the first encrypted data. The blockchain decrypts the first encrypted data according to the symmetric encryption key, obtains the facial feature data of the user, and completes the makeup recommendation;

[0015] Second encryption: The first encrypted data and makeup recommendation content are converted into a hash value of a fixed size using a hash algorithm, and the hash value is stored in a data cluster on the blockchain; different hash values ​​are stored in different data clusters to form a database; each hash value corresponds to a key.

[0016] Optionally, calculating the smoothness of the user's face is to use machine vision to calculate smoothness, uniformity and coherence parameters of the facial skin and soft tissue.

[0017] Optionally, the similarity between the product and the user's facial features and facial makeup is calculated, specifically, multi-dimensional similarities are calculated, including calculating the similarity between facial makeup and makeup color blended with the user's skin color, and the similarity between facial makeup and shadows formed by facial features.

[0018] Optionally, beauty products are recommended based on facial shadow features, color fusion and beauty product characteristics.

[0019] Optionally, the user can transmit his or her own makeup preferences and beauty preferences to the smart beauty mirror through a mobile terminal, and then recommend the best makeup and beauty products.

[0020] An intelligent recommendation system for beauty products based on facial feature extraction, comprising:

[0021] Target makeup and facial feature input module: used to obtain the user's target expected makeup type and the user's facial features using the smart beauty mirror, and double encrypt the user's facial features. The first encryption is used for this makeup recommendation, and the second encryption is used to build a user sample database to calculate the user's facial flatness and facial shadow distribution;

[0022] Facial makeup recommendation module: used to recommend facial makeup based on the calculation results and the target expected makeup type, and present the recommended makeup on the user's face through the smart beauty mirror;

[0023] Beauty product pre-selection module: used to transmit the user's beauty purchase information to the smart beauty mirror MCU through the mobile terminal, analyze the user's historical purchase records and browsing behavior, find other users with similar facial features to the user, and pre-select beauty products;

[0024] Beauty product recommendation module: used to calculate the similarity between the product and the user's facial features and facial makeup based on the recommended facial makeup features and beauty product attributes, and recommend beauty products based on the degree of similarity.

[0025] Optionally, the target makeup and facial feature input module includes a first encryption module and a second encryption module: the first encryption module is used to transmit the facial feature data of the current user to the blockchain using symmetric encryption to obtain first-encrypted data, and the blockchain decrypts the first-encrypted data according to the symmetric encryption key to obtain the user's facial feature data and complete the makeup recommendation; the second encryption module is used to convert the first-encrypted data and the makeup recommendation content into a hash value of a fixed size using a hash algorithm, and store the hash value on the data cluster of the blockchain; different hash values ​​are stored in different data clusters to form a database; each hash value corresponds to a key.

[0026] Optionally, it also includes a user participation module: it is used for users to transmit their makeup preferences and beauty preferences to the smart beauty mirror through a mobile terminal, and then recommend the best makeup and beauty products.

[0027] A computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the computer program implements the steps of any one of the methods for intelligently recommending beauty products based on facial feature extraction.

[0028] It can be seen from the above technical solutions that, compared with the prior art, the present invention provides an intelligent recommendation method, system and storage medium for beauty products based on facial feature extraction, which has the following beneficial effects:

[0029] 1. The smart beauty mirror can obtain the user's target makeup type and facial features, and intelligently recommend makeup that suits the user's personal characteristics and needs.

[0030] 2. Double encryption not only protects the privacy and security of users, but also ensures the effective use of data: the first encryption is used for this makeup recommendation, ensuring the accuracy and real-time nature of the recommendation; the second encryption is used to build a user sample database, providing a basis for future makeup recommendations and beauty product analysis.

[0031] In summary, the present invention utilizes the smart makeup mirror to realize the above functions, which can provide users with a more personalized, accurate and convenient makeup experience, while improving user satisfaction and loyalty. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0033] Figure 1 It is a schematic diagram of the process of the present invention;

[0034] Figure 2 It is a structural schematic diagram of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] The embodiment of the present invention discloses an intelligent recommendation method for beauty products based on facial feature extraction, such as Figure 1 As shown, the following steps are included:

[0037] Step 1: Use the smart makeup mirror to obtain the user's target makeup type and the user's facial features, and perform double encryption on the user's facial features. The first encryption is used for this makeup recommendation, and the second encryption is used to build a user sample database to calculate the user's facial flatness and facial shadow distribution;

[0038] Step 2: recommend facial makeup based on the calculation results and the target expected makeup type, and present the recommended makeup on the user's face through the smart beauty mirror;

[0039] Step 3: The user connects to the smart beauty mirror through a mobile terminal, and transmits the user's beauty purchase information to the smart beauty mirror MCU through the mobile terminal, analyzes the user's historical purchase records and browsing behavior, finds other users with similar facial features to the user, and pre-selects beauty products;

[0040] Step 4: Based on the recommended facial makeup features and beauty product attributes, calculate the similarity between the product and the user's facial features and facial makeup, and recommend beauty products based on the degree of similarity.

[0041] Furthermore, in step 1, the double encryption process of the user's facial features includes:

[0042] First encryption: The facial feature data of the current user is transmitted to the blockchain using symmetric encryption to obtain the first encrypted data. The blockchain decrypts the first encrypted data according to the symmetric encryption key, obtains the facial feature data of the user, and completes the makeup recommendation;

[0043] Second encryption: The first encrypted data and makeup recommendation content are converted into a hash value of a fixed size using a hash algorithm, and the hash value is stored in a data cluster on the blockchain; different hash values ​​are stored in different data clusters to form a database; each hash value corresponds to a key.

[0044] Furthermore, in step one, the user's facial flatness is calculated by using machine vision to calculate smoothness, uniformity and coherence parameters of facial skin and soft tissue.

[0045] Furthermore, in step 2, using artificial intelligence algorithms, the smart beauty mirror will conduct an in-depth analysis of the collected facial feature data. The analysis includes comprehensive skin indexes such as facial flatness, facial shadow distribution, skin health, cleanliness, stability, texture, and brightness. Based on the user's facial feature analysis results and the target makeup type, the smart beauty mirror will use algorithms to match the makeup. During the matching process, multiple factors such as facial features, skin condition, and makeup style will be considered to ensure that the recommended makeup not only meets the user's expectations, but also highlights the user's personal charm.

[0046] Furthermore, in step three, in addition to purchase records, the smart beauty mirror also analyzes the user's browsing behavior, such as browsed pages, dwell time, number of clicks, etc. These data help to understand the user's interest and attention to beauty products.

[0047] The smart makeup mirror uses face recognition technology to extract the user's facial feature data and match it with the facial features of other users stored in the database. The algorithm calculates the similarity of facial features and finds other users with similar facial features to the user.

[0048] Based on the similar user groups found, the smart beauty mirror uses a recommendation algorithm to pre-select beauty products that users may be interested in. The recommendation algorithm takes into account the purchase history, browsing behavior, and current market trends and popular elements of similar users.

[0049] In this embodiment, the smart makeup mirror also includes product display, where the pre-selected makeup products are displayed to the user in the form of a list or image. The user can view the detailed information, price, evaluation, etc. of the product by browsing, clicking, or voice control, and make a purchase decision.

[0050] Furthermore, in step four, the similarity between the product and the user's facial features and facial makeup is calculated, specifically, the similarity in multiple dimensions is calculated, including the similarity between the facial makeup and the makeup color blended with the user's skin color, and the similarity between the facial makeup and the shadows formed by the facial features.

[0051] Furthermore, beauty products are recommended comprehensively based on facial shadow features, color fusion and beauty product characteristics.

[0052] In this embodiment, the user also transmits his or her own makeup preferences and beauty preferences to the smart beauty mirror through the mobile terminal, and then recommends the best makeup and beauty products.

[0053] and Figure 1 Corresponding to the method shown, the present invention also discloses an intelligent recommendation system for beauty products based on facial feature extraction for Figure 1 The implementation of the method, the specific structure is as follows Figure 2 As shown, including:

[0054] Target makeup and facial feature input module: used to obtain the user's target expected makeup type and the user's facial features using the smart beauty mirror, and double encrypt the user's facial features. The first encryption is used for this makeup recommendation, and the second encryption is used to build a user sample database to calculate the user's facial flatness and facial shadow distribution;

[0055] Facial makeup recommendation module: used to recommend facial makeup based on the calculation results and the target expected makeup type, and present the recommended makeup on the user's face through the smart beauty mirror;

[0056] Beauty product pre-selection module: used to transmit the user's beauty purchase information to the smart beauty mirror MCU through the mobile terminal, analyze the user's historical purchase records and browsing behavior, find other users with similar facial features to the user, and pre-select beauty products;

[0057] Beauty product recommendation module: used to calculate the similarity between the product and the user's facial features and facial makeup based on the recommended facial makeup features and beauty product attributes, and recommend beauty products based on the degree of similarity.

[0058] Furthermore, the target makeup and facial feature input module includes a first encryption module and a second encryption module: the first encryption module is used to transmit the facial feature data of the current user to the blockchain using symmetric encryption to obtain first-encrypted data, and the blockchain decrypts the first-encrypted data according to the symmetric encryption key to obtain the user's facial feature data and complete the makeup recommendation; the second encryption module is used to convert the first-encrypted data and the makeup recommendation content into a hash value of a fixed size using a hash algorithm, and store the hash value on the data cluster of the blockchain; different hash values ​​are stored in different data clusters to form a database; each hash value corresponds to a key.

[0059] Furthermore, it also includes a user participation module: it is used for users to transmit their own makeup preferences and beauty preferences to the smart beauty mirror through mobile terminals, and then recommend the best makeup and beauty products.

[0060] This embodiment also includes a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, any one of the steps of the method for intelligently recommending beauty products based on facial feature extraction is implemented.

[0061] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0062] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent recommendation method for beauty products based on facial feature extraction, characterized in that: The following steps are involved: The smart makeup mirror is used to obtain the user's target makeup type and facial features, and the user's facial features are double-encrypted. The first encryption is used for this makeup recommendation, and the second encryption is used to build a user sample database to calculate the user's facial flatness and facial shadow distribution; Recommend facial makeup based on the calculation results and the target expected makeup type, and present the recommended makeup on the user's face through the smart beauty mirror; The user connects to the smart beauty mirror through a mobile terminal, and transmits the user's beauty purchase information to the smart beauty mirror MCU through the mobile terminal, analyzes the user's historical purchase records and browsing behavior, finds other users with similar facial features to the user, and pre-selects beauty products; Based on the recommended facial makeup features and beauty product attributes, the similarity between the product and the user's facial features and facial makeup is calculated, and beauty products are recommended based on the level of similarity.

2. The intelligent recommendation method for beauty products based on facial feature extraction according to claim 1, characterized in that: Double encryption of user facial features includes: First encryption: The facial feature data of the current user is transmitted to the blockchain using symmetric encryption to obtain the first encrypted data. The blockchain decrypts the first encrypted data according to the symmetric encryption key, obtains the facial feature data of the user, and completes the makeup recommendation; Second encryption: The first encrypted data and makeup recommendation content are converted into a hash value of a fixed size using a hash algorithm, and the hash value is stored in a data cluster on the blockchain; different hash values ​​are stored in different data clusters to form a database; each hash value corresponds to a key.

3. The intelligent recommendation method for beauty products based on facial feature extraction according to claim 1, characterized in that: Calculating the user's facial flatness is to use machine vision to calculate the smoothness, uniformity and coherence parameters of the facial skin and soft tissue.

4. The intelligent recommendation method for beauty products based on facial feature extraction according to claim 1, characterized in that: Calculate the similarity between the product and the user's facial features and facial makeup, specifically calculating the similarity in multiple dimensions, including calculating the similarity between the facial makeup and the makeup color blended with the user's skin color, and the similarity between the facial makeup and the shadows formed by the facial features.

5. The intelligent recommendation method for beauty products based on facial feature extraction according to claim 4, characterized in that: Beauty products are recommended comprehensively based on facial shadow characteristics, color fusion and beauty product features.

6. The intelligent recommendation method for beauty products based on facial feature extraction according to claim 1, characterized in that: It also includes users transmitting their makeup preferences and beauty preferences to the smart beauty mirror through mobile terminals, and then recommending the best makeup and beauty products.

7. An intelligent recommendation system for beauty products based on facial feature extraction, characterized in that: include: Target makeup and facial feature input module: used to obtain the user's target expected makeup type and the user's facial features using the smart beauty mirror, and double encrypt the user's facial features. The first encryption is used for this makeup recommendation, and the second encryption is used to build a user sample database to calculate the user's facial flatness and facial shadow distribution; Facial makeup recommendation module: used to recommend facial makeup based on the calculation results and the target expected makeup type, and present the recommended makeup on the user's face through the smart beauty mirror; Beauty product pre-selection module: used to transmit the user's beauty purchase information to the smart beauty mirror MCU through the mobile terminal, analyze the user's historical purchase records and browsing behavior, find other users with similar facial features to the user, and pre-select beauty products; Beauty product recommendation module: used to calculate the similarity between the product and the user's facial features and facial makeup based on the recommended facial makeup features and beauty product attributes, and recommend beauty products based on the degree of similarity.

8. The intelligent recommendation system for beauty products based on facial feature extraction according to claim 7, characterized in that: The target makeup and facial feature input module includes a first encryption module and a second encryption module: the first encryption module is used to transmit the facial feature data of the current user to the blockchain using symmetric encryption to obtain the first encrypted data. The blockchain decrypts the first encrypted data according to the symmetric encryption key to obtain the facial feature data of the user and complete the makeup recommendation; The second encryption module is used to convert the first encrypted data and the makeup recommendation content into a hash value of a fixed size using a hash algorithm, and store the hash value in a data cluster of the blockchain; Different hash values ​​are stored in different data clusters to form a database; each hash value corresponds to a key.

9. The intelligent recommendation system for beauty products based on facial feature extraction according to claim 7, characterized in that: It also includes a user participation module: it is used for users to transmit their makeup preferences and beauty preferences to the smart beauty mirror through mobile terminals, and then recommend the best makeup and beauty products.

10. A computer storage medium, characterized in that: The computer storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the method for intelligently recommending beauty products based on facial feature extraction as described in any one of claims 1 to 6 are implemented.

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