CN112633975A - Personalized clothing shopping guide system based on data analysis - Google Patents
Personalized clothing shopping guide system based on data analysis Download PDFInfo
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- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
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- G06F16/95—Retrieval from the web
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- G06F16/9535—Search customisation based on user profiles and personalisation
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0641—Shopping interfaces
- G06Q30/0643—Graphical representation of items or shoppers
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
Abstract
The invention discloses a personalized clothing shopping guide system based on data analysis, which comprises an image acquisition module, an image processing module, a user information input module, a model template database, a similarity processing module and a clothing matching pushing module, wherein the image acquisition module is used for acquiring a whole-body image of a user, the image processing module is used for identifying the whole-body image of the user and extracting information, the user information input module is used for the user to input basic information, the model template database comprises model template basic information and a clothing matching template, the similarity processing module calculates the overall similarity between the user and the model template basic information according to the information extracted by the image processing module and the basic information input by the user information input module, and screens the model template basic information according to the overall similarity.
Description
Technical Field
The invention relates to the field of data analysis, in particular to a personalized clothing shopping guide system based on data analysis.
Background
In the traditional clothes purchasing process, a customer needs to go to a clothes purchasing site, selects favorite clothes firstly, then takes off the clothes on the body, tries on new clothes, occupies a large amount of time for the customer, and can purchase a piece of clothes suitable for the customer in many hours. At present, with the development of network technology, more and more people choose to buy clothes on the internet, but when the clothes are bought on the internet, people can not only wear the clothes or the clothes are suitable for themselves, but also the clothes can be matched in what way, so that the clothes are worried.
Disclosure of Invention
The invention aims to provide a personalized clothing shopping guide system and a personalized clothing shopping guide method based on data analysis, so as to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme:
a personalized clothing shopping guide system based on data analysis comprises an image acquisition module, an image processing module, a user information input module, a model template database, a similarity processing module and a clothing matching pushing module, wherein the image acquisition module is used for acquiring a whole body image of a user, the image processing module is used for identifying the whole body image of the user and extracting information, the user information input module is used for the user to input basic information, the model template database comprises model template basic information and a clothing matching template, the similarity processing module calculates the overall similarity between the user and the model template basic information according to the information extracted by the image processing module and the basic information input by the user information input module and screens the model template basic information according to the overall similarity, the clothing matching pushing module acquires a corresponding clothing matching template according to the screened model template basic information, and further screening the clothing matching template, and presenting the screened clothing matching template to the user.
Preferably, the image processing module comprises a facial feature extraction module and a body part contour information extraction module, the facial feature extraction module is used for obtaining the face shape of the user, the body part contour information extraction module is used for obtaining the shoulder width, hip circumference, chest circumference, waist circumference, thigh circumference and shank circumference of the user, the user information input module is used for the user to input the sex, height information and weight of the user, the similarity processing module comprises a body similarity calculation module, a facial feature similarity calculation module, a body part contour similarity calculation module, an overall similarity calculation module and a similarity screening module, the body similarity calculation module calculates the body similarity according to the height information and the weight, the facial feature similarity calculation module calculates the facial feature similarity according to the face shape, the body part contour similarity calculation module calculates the facial feature similarity according to the shoulder width, the thigh circumference and the weight, the body part contour similarity calculation module calculates the facial feature similarity according to the shoulder width and the thigh circumference, The model template comprises a hip circumference, a chest circumference, a waist circumference, a thigh circumference and a shank circumference, wherein the body part contour similarity is calculated by the hip circumference, the chest circumference, the waist circumference, the thigh circumference and the shank circumference, the overall similarity calculation module is used for comparing the overall similarity with a similarity threshold value according to the body shape similarity, the face feature similarity and the body part contour similarity, and the model template basic information with the overall similarity larger than the similarity threshold value is screened out by the similarity screening module.
Preferably, the clothing matching pushing module comprises a clothing matching template obtaining module, a clothing matching template scoring module, a browsing timing module, a favorite value calculating module and a clothing matching template screening module, the clothing matching template acquisition module is used for acquiring the clothing matching templates corresponding to the model template basic information larger than the similarity threshold value and presenting the clothing matching templates to a user for watching, the clothing matching template scoring module is used for scoring the presented clothing matching template by the user, the browsing timing module times the time of the user browsing each set of clothes matching template, the favorite value calculating module calculates the favorite value according to the score and the browsing time of each set of clothes matching template, the clothing matching template screening module screens out the first 5 sets of clothing matching templates with favorite values from top to bottom, and sequentially presenting the 5 sets of clothes matching templates to the user according to the sequence of scores from top to bottom.
A personalized garment shopping guide method based on data analysis, the garment shopping guide method comprising the steps of:
step S1: the camera shoots a user, obtains a whole body image of the user, performs face recognition on the whole body image of the user and extracts face characteristic information from the whole body image of the user, performs body part recognition on the whole body image of the user and extracts contour information of each body part from the whole body image of the user;
step S2: inputting user basic information, wherein the user basic information comprises user gender, height information and weight, and the height information comprises user height, user upper body length and user lower body length;
step S3: screening model template basic information consistent with the gender of a user from a model template database prestored with a plurality of model template basic information, and calculating the overall similarity z1 of the user and the model template basic information according to the facial feature information, the body part contour information and the user basic information;
step S4: the method comprises the steps of screening model template basic information with overall similarity z1 larger than a similarity threshold value from the model template basic information, obtaining clothes matching templates corresponding to the model template basic information and presenting the clothes matching templates to a user for watching, scoring the presented clothes matching templates by the user, screening the front 10 sets of clothes matching templates with scores from top to bottom, respectively obtaining the browsing time of the user for watching the 10 sets of clothes matching templates, calculating the favorite value W of the user for each set of clothes matching template, screening the front 5 sets of clothes matching templates with favorite values from top to bottom, and sequentially presenting the 5 sets of clothes matching templates to the user according to the sequence of scores from top to bottom, wherein when the user watches the favorite clothes matching templates, the user tends to spend more time for watching, and therefore the browsing time is used as a favorite value reference factor.
Preferably, the step S3 of calculating the overall similarity z1 between the user and the model template includes the following steps:
step S31: calculating the stature similarity x1= a1S0+ a2S1+ a3S3+ a4M + a5Q,
wherein S0 is the height similarity, S1 is the upper body length similarity, S3 is the lower body length similarity of the user, M is the weight similarity of the user, and Q is the similarity of the ratio of the upper body length to the lower body length of the user; a1 is the weight occupied by the height similarity, a2 is the weight occupied by the length similarity of the upper body of the user, a3 is the weight occupied by the length similarity of the lower body of the user, a4 is the weight occupied by the weight similarity of the weight of the user, and a5 is the weight occupied by the similarity of the ratio of the length of the upper body of the user to the length of the lower body of the user; in many cases, the height is the same, but the ratio of the upper body length to the lower body length is often quite different, and different clothing matching manners should be adopted for the situation, so that the ratio of the upper body length to the lower body length of the user is used as a reference factor of the body similarity.
Step S32: overall similarity z1= b1x1+ b2x2+ b3x3 is calculated,
wherein x1 is the figure similarity, x2 is the facial feature similarity, x3 is the body part contour similarity, b1 is the weight occupied by the figure similarity, b2 is the weight occupied by the facial feature similarity, b3 is the weight occupied by the body part contour similarity, and the overall similarity is considered from three aspects of the figure similarity, the facial feature similarity and the body part contour similarity, so that the model template basic information is screened out more specifically and reasonably.
Preferably, in the step S4, the user' S favorite value W = v1T/T for each set of clothing matching template, where v1 is the score of the set of clothing matching template, T is the browsing time of the user viewing the set of clothing matching template, and T is the total browsing time of the user viewing the 10 sets of clothing matching templates.
Preferably, the facial feature information includes a face shape, and the body contour information includes a shoulder width, a hip circumference, a chest circumference, a waist circumference, a thigh circumference, and a shank circumference.
Preferably, the facial feature similarity x2 is a similarity of face shape, the body contour similarity x3= f1p1+ f2p2+ f3p3+ f4p4, wherein p1 is a similarity of a ratio of shoulder width to hip circumference, p2 is a similarity of chest circumference, p3 is a similarity of waist circumference, p4 is a similarity of a ratio of thigh circumference to calf circumference, f1 is a weight of a similarity of a ratio of shoulder width to hip circumference, f2 is a weight of similarity of chest circumference, f3 is a weight of similarity of waist circumference, and f4 is a weight of similarity of a ratio of thigh circumference to calf circumference.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the overall similarity is considered from three aspects of the figure similarity, the face feature similarity and the body part outline similarity, so that the model template basic information is screened, the screened model template basic information is relatively similar to the user overall, and the clothes matching template favored by the user is screened from the clothes matching templates corresponding to the model template basic information according to the grading and browsing time of the user, so that the invention is more personalized, and the user does not need to try on clothes and match clothes in person, thereby saving a great deal of time of the user.
Drawings
FIG. 1 is a schematic block diagram of a personalized clothing shopping guide system based on data analysis according to the present invention;
fig. 2 is a schematic flow chart of a personalized clothing shopping guide method based on data analysis according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
Referring to fig. 1-2, in an embodiment of the present invention, a personalized clothing shopping guide system based on data analysis includes an image acquisition module, an image processing module, a user information input module, a model template database, a similarity processing module and a clothing matching pushing module, the image acquisition module is configured to acquire a whole-body image of a user, the image processing module is configured to identify the whole-body image of the user and extract information, the user information input module is configured for the user to input basic information, the model template database includes model template basic information and a clothing matching template, the similarity processing module calculates an overall similarity between the user and the model template basic information according to the information extracted by the image processing module and the basic information input by the user information input module, and screens the model template basic information according to the overall similarity, and the clothing matching pushing module acquires the corresponding clothing matching template according to the basic information of the screened model template, further screens the clothing matching template, and presents the screened clothing matching template to the user.
The image processing module comprises a facial feature extraction module and a body part contour information extraction module, the facial feature extraction module is used for acquiring the face shape of a user, the body part contour information extraction module is used for acquiring the shoulder width, hip circumference, chest circumference, waist circumference, thigh circumference and shank circumference of the user, the user information input module is used for the user to input the sex, height information and weight of the user, the similarity processing module comprises a body similarity calculation module, a facial feature similarity calculation module, a body part contour similarity calculation module, an overall similarity calculation module and a similarity screening module, the body similarity calculation module calculates the body similarity according to the height information and the weight, the facial feature similarity calculation module calculates the facial feature similarity according to the face shape, the body part contour similarity calculation module calculates the facial feature similarity according to the shoulder width, the waist circumference, the thigh circumference and the shank circumference, the body similarity calculation module calculates the body contour similarity according to the shoulder width and the, The model template comprises a hip circumference, a chest circumference, a waist circumference, a thigh circumference and a shank circumference, wherein the body part contour similarity is calculated by the hip circumference, the chest circumference, the waist circumference, the thigh circumference and the shank circumference, the overall similarity calculation module is used for comparing the overall similarity with a similarity threshold value according to the body shape similarity, the face feature similarity and the body part contour similarity, and the model template basic information with the overall similarity larger than the similarity threshold value is screened out by the similarity screening module.
The clothing matching pushing module comprises a clothing matching template obtaining module, a clothing matching template scoring module, a browsing timing module, a favorite value calculating module and a clothing matching template screening module, the clothing matching template acquisition module is used for acquiring the clothing matching templates corresponding to the model template basic information larger than the similarity threshold value and presenting the clothing matching templates to a user for watching, the clothing matching template scoring module is used for scoring the presented clothing matching template by the user, the browsing timing module times the time of the user browsing each set of clothes matching template, the favorite value calculating module calculates the favorite value according to the score and the browsing time of each set of clothes matching template, the clothing matching template screening module screens out the first 5 sets of clothing matching templates with favorite values from top to bottom, and sequentially presenting the 5 sets of clothes matching templates to the user according to the sequence of scores from top to bottom.
A personalized garment shopping guide method based on data analysis, the garment shopping guide method comprising the steps of:
step S1: the method comprises the steps that a camera shoots a user, a whole-body image of the user is obtained, the face of the whole-body image of the user is identified, face characteristic information is extracted from the whole-body image of the user, body part identification is carried out on the whole-body image of the user, and body part contour information is extracted from the whole-body image of the user, wherein the face characteristic information comprises a face shape, and the body part contour information comprises shoulder width, hip circumference, chest circumference, waist circumference, thigh circumference and shank circumference;
step S2: inputting user basic information, wherein the user basic information comprises user gender, height information and weight, and the height information comprises user height, user upper body length and user lower body length;
step S3: screening model template basic information consistent with the gender of the user from a model template database prestored with a plurality of model template basic information, and calculating the overall similarity z1 between the user and the model template basic information according to the facial feature information, the body part contour information and the user basic information:
the calculation of the overall similarity z1 between the user and the model template comprises the following steps:
step S31: calculating figure similarity
x1=0.3S0+0.1S1+0.1S3+0.2M+0.3Q,
Wherein S0 is the height similarity, S1 is the upper body length similarity, S3 is the lower body length similarity of the user, M is the weight similarity of the user, and Q is the similarity of the ratio of the upper body length to the lower body length of the user;
step S32: the overall similarity z1=0.45x1+0.2x2+0.35x3 was calculated,
wherein x1 is the figure similarity, x2 is the face feature similarity, x3 is the body part contour similarity,
the facial feature similarity x2 is similarity of face shape, the body part contour similarity x3=0.25p1+0.25p2+0.25p3+0.25p4, wherein p1 is similarity of ratio of shoulder width to hip circumference, p2 is similarity of chest circumference, p3 is similarity of waist circumference, and p4 is similarity of ratio of thigh circumference to calf circumference;
step S4: selecting model template basic information with the overall similarity z1 larger than a similarity threshold from the model template basic information, acquiring the clothing matching templates corresponding to the model template basic information and presenting the clothing matching templates to a user for watching, scoring the presented clothing matching templates by the user, selecting the top 10 sets of clothing matching templates with the scores from top to bottom, respectively acquiring the browsing time of the user for watching the 10 sets of clothing matching templates, calculating the favorite value W of the user for each set of clothing matching template,
the user's preference value W = v1T/T for each suit match template, wherein v1 is the score of the suit match template, T is the browsing time of the user watching the suit match template, T is the total browsing time of the user watching the 10 suit match templates,
the first 5 sets of clothes matching templates with the favorite value scores from top to bottom are screened out, and the 5 sets of clothes matching templates are sequentially presented to the user according to the sequence of the scores from top to bottom.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (1)
1. The personalized clothing shopping guide system based on data analysis is characterized in that: the clothing shopping guide system comprises an image acquisition module, an image processing module, a user information input module, a model template database, a similarity processing module and a clothing matching pushing module, wherein the image acquisition module is used for acquiring a whole-body image of a user, the image processing module is used for identifying the whole-body image of the user and extracting information, the user information input module is used for the user to input basic information, the model template database comprises model template basic information and a clothing matching template, the similarity processing module calculates the overall similarity between the user and the model template basic information according to the information extracted by the image processing module and the basic information input by the user information input module and screens the model template basic information according to the overall similarity, the clothing matching pushing module acquires a corresponding clothing template according to the screened model template basic information, further screening the clothing matching template, and presenting the screened clothing matching template to a user;
the shopping guide method of the personalized clothing shopping guide system comprises the following steps:
step S1: the camera shoots a user, obtains a whole body image of the user, performs face recognition on the whole body image of the user and extracts face characteristic information from the whole body image of the user, performs body part recognition on the whole body image of the user and extracts contour information of each body part from the whole body image of the user;
step S2: inputting user basic information, wherein the user basic information comprises user gender, height information and weight, and the height information comprises user height, user upper body length and user lower body length;
step S3: screening model template basic information consistent with the gender of a user from a model template database prestored with a plurality of model template basic information, and calculating the overall similarity z1 of the user and the model template basic information according to the facial feature information, the body part contour information and the user basic information;
step S4: selecting model template basic information with overall similarity z1 larger than a similarity threshold value from the model template basic information, acquiring clothes matching templates corresponding to the model template basic information and presenting the clothes matching templates to a user for watching, scoring the presented clothes matching templates by the user, selecting the front 10 sets of clothes matching templates with scores from top to bottom, respectively acquiring the browsing time of the user for watching the 10 sets of clothes matching templates, calculating the favorite value W of the user for each set of clothes matching template, screening the front 5 sets of clothes matching templates with favorite values from top to bottom, and sequentially presenting the 5 sets of clothes matching templates to the user according to the sequence of scores from top to bottom;
the step S3 of calculating the overall similarity z1 between the user and the model template comprises the following steps:
step S31: calculating the stature similarity x1= a1S0+ a2S1+ a3S3+ a4M + a5Q,
wherein S0 is the height similarity, S1 is the upper body length similarity, S3 is the lower body length similarity of the user, M is the weight similarity of the user, and Q is the similarity of the ratio of the upper body length to the lower body length of the user; a1 is the weight occupied by the height similarity, a2 is the weight occupied by the length similarity of the upper body of the user, a3 is the weight occupied by the length similarity of the lower body of the user, a4 is the weight occupied by the weight similarity of the weight of the user, and a5 is the weight occupied by the similarity of the ratio of the length of the upper body of the user to the length of the lower body of the user;
step S32: overall similarity z1= b1x1+ b2x2+ b3x3 is calculated,
wherein x1 is the figure similarity, x2 is the face feature similarity, x3 is the body part contour similarity, b1 is the weight occupied by the figure similarity, b2 is the weight occupied by the face feature similarity, and b3 is the weight occupied by the body part contour similarity;
in the step S4, the favorite value W = v1T/T of the user for each set of clothing matching template, where v1 is the score of the set of clothing matching template, T is the browsing time of the user viewing the set of clothing matching template, and T is the total browsing time of the user viewing the 10 sets of clothing matching templates;
the facial feature information comprises a face shape, and the body part contour information comprises shoulder width, hip circumference, chest circumference, waist circumference, thigh circumference and shank circumference;
the facial feature similarity x2 is similarity of face shape, the body part contour similarity x3= f1p1+ f2p2+ f3p3+ f4p4, wherein p1 is similarity of a ratio of shoulder width to hip circumference, p2 is similarity of chest circumference, p3 is similarity of waist circumference, p4 is similarity of a ratio of thigh circumference to calf circumference, f1 is weight occupied by similarity of a ratio of shoulder width to hip circumference, f2 is weight occupied by similarity of chest circumference, f3 is weight occupied by similarity of waist circumference, and f4 is weight occupied by similarity of a ratio of thigh circumference to calf circumference.
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