CN113822726A - Shopping guide method and system for shopping mall, storage medium and electronic equipment - Google Patents
Shopping guide method and system for shopping mall, storage medium and electronic equipment Download PDFInfo
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Abstract
The application discloses a shopping guide method, a shopping guide system, a storage medium and electronic equipment for a shopping mall, wherein the method comprises the following steps: a business opportunity obtaining step: the collection step comprises: acquiring human faces of people watching 3D advertisements outside a business city to obtain a plurality of pieces of first human face image information; and (3) association step: performing figure drawing on the first face image information by a face recognition technology to obtain a figure drawing corresponding to each first face image information, and associating the figure drawing with advertisement information of the 3D advertisement to obtain associated data; a display step: and acquiring second face image information of each customer entering the mall, judging whether each second face image information is matched with one of the plurality of associated data, and outputting and displaying the SD advertisement and store information corresponding to the SD advertisement when the second face image information is matched with one of the associated data. The invention shows the latest popular advertisement products to the customers in a 3D stereo form, and realizes the accurate delivery of the advertisements.
Description
Technical Field
The invention belongs to the field of shopping guide of a shopping mall, and particularly relates to a shopping guide method and system of the shopping mall, a storage medium and electronic equipment.
Background
In recent years, the internet of things (IOT) technology is widely applied, and smart homes, smart medical supplies and the like enter the world of everything interconnection. Internet advertising traffic entry 80% has been dominated by hundredths, ali, Tencent. Only under the line, the Internet of things advertisement is still in the gradual development, and particularly, the advertisement of each shopping mall is fixed in advertisement position and content, various in type, lack of communication with the consumer with the most shopping motivation and accurate advertisement push guidance. By taking the latest 3D naked-eye large-screen advertisement introduced in Beijing Taigu and Chengdu Taigu as an example, the latest popular advertisement is put in, the latest product is presented to consumers in a three-dimensional effect, and dynamic guidance of the advertisement is realized while the consumers actively select the advertisement. If on this basis do accurate portrait, watch time and the little table feelings analysis and judge the product that every consumer liked to 3D advertisement audience crowd through face identification, at the time that the consumer got into the mall, through shopping guide of mall robot, the inside advertisement screen in mall, elevator inside advertisement etc. based on internet of things, real-time, on the spot, the dynamic product advertisement of liking to the customer is put in and is guided, realize the initiative propelling movement of product and the accurate of advertisement and put in.
The prior art is as follows:
1. fixed advertisement positions are arranged outside the mall, each advertisement position puts a fixed advertisement, and the content of some advertisement positions is replaced manually at regular intervals;
2. an electronic screen is arranged in the mall and is used for playing advertisements in a fixed and circulating manner;
3. the shopping guide robot and other equipment in the mall are fixed to publicize advertisements for customers;
the problems existing in the prior art are as follows:
the existing shopping mall has fixed advertisement positions, old contents, complexity, lack of emphasis and lack of accurate advertisement delivery; the popular novel advertisement cannot be displayed in real time, is lack of stereoscopic impression and attraction, and is lack of real-time popularization of the advertisement; the existing advertisement space can not effectively detect audience and crowd; the existing advertisement space passively crashes to wait for a client, and lacks a process of actively pushing hot products to the client; the advertisement putting effect is difficult to measure, and the audience population statistics is difficult.
Disclosure of Invention
The embodiment of the application provides a shopping guide method, a shopping guide system, a storage medium and electronic equipment, which are used for at least solving the problems of fixed advertisement space, old content, complexity, lack of emphasis and lack of accurate advertisement putting of the conventional shopping guide method.
The invention provides a shopping guide method for a shopping mall, which comprises the following steps:
the collection step comprises: acquiring human faces of people watching 3D advertisements outside a business city to obtain a plurality of pieces of first human face image information;
and (3) association step: performing figure drawing on the first face image information by a face recognition technology to obtain a figure drawing corresponding to each first face image information, and associating the figure drawing with advertisement information of the 3D advertisement to obtain associated data;
a display step: and acquiring second face image information of each customer entering the mall, judging whether each second face image information is matched with one of the plurality of associated data, and outputting and displaying the SD advertisement and store information corresponding to the SD advertisement when the second face image information is matched with one of the associated data.
The shopping guide method for the shopping mall further comprises the following steps:
a consumption result information acquisition step: and acquiring third facial image information of a customer entering a store, judging whether the third facial image information is matched with one of the plurality of associated data, and acquiring and storing consumption result information of the customer corresponding to the associated data during matching and then outputting the consumption result information to an information platform of the store.
The shopping guide method for the shopping mall further comprises the following steps:
a step of acquiring statistical information: and binding the consumption result information and the associated data corresponding to the consumption result information to form statistical result information, and outputting the statistical result information to an information platform of the mall.
The shopping guide method for the shopping mall, wherein the associating step includes:
an advertisement information acquisition step: collecting the advertisement information corresponding to the 3D advertisement;
a figure portrait acquisition step: performing figure drawing on the first face image information by using face features, micro-expression features, time features and task features of the first face image information based on a face recognition technology to obtain the figure drawing;
and a step of acquiring associated data: and associating the character image with the advertisement information to obtain and store the associated data.
The shopping guide method for the mall, wherein the displaying step further comprises:
a second face image information acquisition step: collecting the second face image information;
a first judgment step: judging whether each piece of second face image information is matched with one of the associated data or not and outputting a matching result;
an information display step: and when the matching result is consistent, outputting the SD advertisement and the store information.
The shopping guide method for the shopping mall, wherein the store information includes: and the product information, the store address information and the route information for going to the store corresponding to the SD advertisement.
The shopping guide method for the mall, wherein the displaying step further comprises:
a fourth face image information acquisition step: collecting fourth face image information of the customer traveling along the route information;
a second judgment step: judging whether each fourth face image information is matched with one of the associated data or not and outputting a matching result;
store information display step: and when the matching result is consistent, outputting at least one corresponding one of the product information, the store address information and the route information to at least one display terminal in the commercial city, and playing the store information through the display terminal.
The invention also provides a shopping guide system for the shopping mall, which comprises the following components:
the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring the faces of people watching 3D advertisements outside a commercial city to obtain a plurality of pieces of first face image information;
the association module is used for performing figure drawing on the first face image information through a face recognition technology to obtain a figure drawing corresponding to each piece of the first face image information, and associating the figure drawing with the advertisement information of the 3D advertisement to obtain association data;
and the display module is used for acquiring second face image information of each customer entering the mall, judging whether each second face image information is matched with one of the plurality of associated data, and outputting and displaying the SD advertisement and store information corresponding to the SD advertisement when the second face image information is matched with one of the associated data.
The 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 processor implements the shopping guide method of the mall as described in any one of the above when executing the computer program.
The present invention also provides a storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the shopping guide method of the mall as described in any one of the above.
The invention has the beneficial effects that:
the invention belongs to the field of basic operation and maintenance in cloud service capacity. The invention solves the problems that the fixed content of the advertisement space is old and the latest product characteristics can not be accurately displayed for the client; the invention shows the latest popular advertisement products to the customers in a 3D stereo form, thereby realizing the accurate delivery of the advertisements; the system takes the Internet of things as a basis, and actively guides the customers to consume in an all-around manner, and the watch is passively active, so that the situation that the products in the store passively wait for the customers to consume at home before is broken, the latest popular products are actively pushed to the customers, and the customers are guided to accurately consume, and the accurate popularization in the product meaning is realized; the invention is beneficial to the accurate statistical analysis of the advertisement effect.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application.
In the drawings:
FIG. 1 is a flow chart of a mall shopping guide method of the present invention;
FIG. 2 is a flowchart of substep S2 of the present invention;
FIG. 3 is a flowchart of substep S3 of the present invention;
FIG. 4 is a schematic illustration of a mall shopping guide method of the present invention;
FIG. 5 is a flow chart of second hand server face recognition technology service interaction;
FIG. 6 is a second hand service face recognition schematic;
FIG. 7 is a second hand service flow conversion snowball theoretical graph;
FIG. 8 is a second hand server face recognition technology architecture diagram;
FIG. 9 is a schematic diagram of the shopping mall shopping guide system of the present invention;
fig. 10 is a frame diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application.
It is obvious that the drawings in the following description are only examples or embodiments of the present application, and that it is also possible for a person skilled in the art to apply the present application to other similar contexts on the basis of these drawings without inventive effort. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of ordinary skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms referred to herein shall have the ordinary meaning as understood by those of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar words throughout this application are not to be construed as limiting in number, and may refer to the singular or the plural. The present application is directed to the use of the terms "including," "comprising," "having," and any variations thereof, which are intended to cover non-exclusive inclusions; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Reference to "connected," "coupled," and the like in this application is not intended to be limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as referred to herein means two or more. "and/or" describes an association relationship of associated objects, meaning that three relationships may exist, for example, "A and/or B" may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. Reference herein to the terms "first," "second," "third," and the like, are merely to distinguish similar objects and do not denote a particular ordering for the objects.
The present invention is described in detail with reference to the embodiments shown in the drawings, but it should be understood that these embodiments are not intended to limit the present invention, and those skilled in the art should understand that functional, methodological, or structural equivalents or substitutions made by these embodiments are within the scope of the present invention.
Before describing in detail the various embodiments of the present invention, the core inventive concepts of the present invention are summarized and described in detail by the following several embodiments.
The first embodiment is as follows:
referring to fig. 1, fig. 1 is a flowchart of a shopping guide method in a mall. As shown in fig. 1, the shopping guide method of the mall of the present invention includes:
a collection step S1: acquiring human faces of people watching 3D advertisements outside a business city to obtain a plurality of pieces of first human face image information;
association step S2: performing figure drawing on the first face image information by a face recognition technology to obtain a figure drawing corresponding to each first face image information, and associating the figure drawing with advertisement information of the 3D advertisement to obtain associated data;
display step S3: acquiring second face image information of each customer entering the mall, judging whether each second face image information is matched with one of the associated data, and outputting and displaying the SD advertisement and store information corresponding to the SD advertisement when the second face image information is matched with one of the associated data;
consumption result information acquisition step S4: acquiring third facial image information of a customer entering a store, judging whether the third facial image information is matched with one of the associated data, and acquiring and storing consumption result information of the customer corresponding to the associated data when the third facial image information is matched with one of the associated data and outputting the consumption result information to an information platform of the store;
statistical information acquisition step S5: and binding the consumption result information and the associated data corresponding to the consumption result information to form statistical result information, and outputting the statistical result information to an information platform of the mall.
Referring to fig. 2, fig. 2 is a flowchart of the associating step S2. As shown in fig. 2, the associating step includes:
advertisement information acquisition step S21: collecting the advertisement information corresponding to the 3D advertisement;
person image acquisition step S22: performing figure drawing on the first face image information by using face features, micro-expression features, time features and task features of the first face image information based on a face recognition technology to obtain the figure drawing;
associated data acquisition step S23: and associating the character image with the advertisement information to obtain and store the associated data.
Referring to fig. 3, fig. 3 is a flowchart showing step S3. As shown in fig. 3, the displaying step S3 includes:
second face image information acquisition step S31: collecting the second face image information;
first determination step S32: judging whether each piece of second face image information is matched with one of the associated data or not and outputting a matching result;
information display step S33: when the matching results are consistent, outputting the SD advertisement and the store information;
fourth face image information acquisition step S34: collecting fourth face image information of the customer traveling along the route information;
second determination step S35: judging whether each fourth face image information is matched with one of the associated data or not and outputting a matching result;
store information display step S36: and when the matching result is consistent, outputting at least one corresponding one of the product information, the store address information and the route information to at least one display terminal in the commercial city, and playing the store information through the display terminal.
Wherein the store information includes: and the product information, the store address information and the route information for going to the store corresponding to the SD advertisement.
Specifically, as shown in fig. 4, the method comprises the following steps:
1. adding a second hand monitoring code to external equipment in the mall;
2. 3D naked eye advertisement is carried out outside the mall and recently popular advertisement products are played, and the three-dimensional stereoscopic impression and the technological sense of the products are perfectly presented by the 3D advertisement technology, so that the intended customers, potential customers and the like are attracted as much as possible. The method comprises the steps of collecting and watching photos of advertisement figures through a camera;
3. the photos are uploaded to a second hand server and simultaneously carry the advertisement id and the advertisement time, and the second hand server carries out figure drawing by face recognition to confirm the audience object. Each portrait is associated with advertisement information (advertisement id + time), and a database is stored:
distinguishing people who are interested in the advertisement at the moment in the image through face and micro-expression recognition;
whether the person is interested in the advertisement product can be indirectly analyzed through the time when the person watches the video;
by task characteristics, gender and age range (adults, old people and children) of the people can be distinguished;
4. the shopping guide robot shoots a photo of a character through a camera and uploads the photo to a second hand server for picture comparison, returns the advertisement information watched by the character, prompts the robot to continuously play the corresponding advertisement through the Internet of things technology, and guides the character to take a mode and a route of a staircase, an elevator and the like specifically reaching a shop;
5. when a customer takes the escalator and the elevator, people and pictures are collected by the camera and are synchronously compared with the second hand server to carry out people and picture contrast, the information of the customer intention advertising products is returned, the playing and the continuous guiding of the route are carried out by the advertising screen in the elevator and the advertising screen at the end of the escalator, meanwhile, the elevator automatically reaches the floor where the advertising products are located, and the shopping guide robot guides the customer to the store to visit the products;
6. after a customer arrives at a store for consumption, a camera of a product store collects photos of characters and uploads the photos to a second hand server for human-image comparison, the second hand server compares and confirms the real consumption of the customer and stores data, and finally, the result is returned to the mall;
7. twelve o 'clock evening every day, second hand server carries out report statistics and sends to the mall to today's 3D naked eye advertisement detection and consumption result.
Further, a second hand server face recognition technology service interaction flow chart is shown in fig. 5, and the second hand server functions as follows:
the mall collects customer information through a camera, and calls a user unique identifier to upload the user information to a second hand server through a local second hand SDK;
the second hand server stores user data and performs writing operation to a magnetic disk and cache operation;
the second hand service acquires user information through an http request, performs data sampling and face recognition, and calculates to obtain a unique uid of the user;
returning the historical watching record corresponding to the user uid to the client;
the client obtains a user history record and carries out targeted advertisement putting;
still further, as shown in a schematic diagram of face recognition in the second hand service shown in fig. 6, the principle specifically used for face recognition is as follows:
face recognition is a biometric technology for identity recognition based on facial feature information of a person. A series of related technologies, also commonly called face recognition and face recognition, are used to capture an image or video stream containing a face with a camera or a video camera, automatically detect and track the face in the image, and then perform face recognition on the detected face.
The face recognition system mainly comprises four components, which are respectively: the method comprises the steps of face image acquisition and detection, face image preprocessing, face image feature extraction, matching and identification.
Preprocessing a face image: the image preprocessing for the human face is a process of processing the image based on the human face detection result and finally serving for feature extraction. The original image acquired by the system is limited by various conditions and random interference, so that the original image cannot be directly used, and the original image needs to be subjected to image preprocessing such as gray scale correction, noise filtering and the like in the early stage of image processing. For the face image, the preprocessing process mainly includes light compensation, gray level transformation, histogram equalization, normalization, geometric correction, filtering, sharpening, and the like of the face image.
Extracting the features of the face image: features that can be used by a face recognition system are generally classified into visual features, pixel statistical features, face image transform coefficient features, face image algebraic features, and the like. The face feature extraction is performed on some features of the face. Face feature extraction, also known as face characterization, is a process of feature modeling for a face. The methods for extracting human face features are classified into two main categories: one is a knowledge-based characterization method; the other is a characterization method based on algebraic features or statistical learning.
Matching and identifying the face image: and searching and matching the extracted feature data of the face image with a feature template stored in a database, and outputting a result obtained by matching when the similarity exceeds a threshold value by setting the threshold value. The face recognition is to compare the face features to be recognized with the obtained face feature template, and judge the identity information of the face according to the similarity degree. This process is divided into two categories: one is confirmation, which is a process of performing one-to-one image comparison, and the other is recognition, which is a process of performing one-to-many image matching comparison.
Still further, as shown in FIG. 7, the second hand analysis is mainly performed for the accurate analysis of the client and the market, and mainly comprises crowd positioning, social media, and traffic precipitation
The private customers are subjected to crowd positioning and advertisement media use, so that advertisements are accurately put, finally, brand efficiency conversion is realized, and the flow is actively drawn close to the product
Whole flow circulation time sequence theoretical diagram for second hand service based on three relations of private domain flow
The second hand server face recognition technique as shown in fig. 8 is as follows:
the second hand service architecture mainly comprises four layers of structures including a vision technology, an algorithm model, a learning framework and an infrastructure
The vision technology mainly depends on hardware, face recognition and the like to collect and mark user basic information and carry out persistent storage
The algorithm model mainly provides basic algorithm acquisition service for face Recognition, and mainly comprises a Recognition algorithm (Feature-based Recognition algorithms) based on human face characteristic points, a Recognition algorithm (application-based Recognition algorithms) based on the whole face image, a Recognition algorithm (Template-based Recognition algorithms) based on templates, and an algorithm (Recognition algorithms using neural network) for Recognition by utilizing a neural network
The second hand service realizes an illumination preprocessing method based on Gamma gray correction, and performs corresponding illumination compensation and illumination balance strategies on the basis of an illumination estimation model
Learning framework based on neural network for automatic feature extraction of multimedia video pictures
The infrastructure adopts cloud computing and distributed deployment aiming at high concurrency and big data to solve the big data request
Example two:
referring to fig. 9, fig. 9 is a schematic structural diagram of a shopping guide system in a mall according to the present invention. Fig. 9 shows a shopping guide system in a mall according to the present invention, which includes:
the system comprises an acquisition module 11, a display module and a display module, wherein the acquisition module 11 is used for acquiring human faces of people watching 3D advertisements outside a city of a merchant to obtain a plurality of pieces of first human face image information;
the association module 12, the association module 12 performs person image drawing on the first face image information by using a face recognition technology to obtain a person image corresponding to each first face image information, and associates the person image with the advertisement information of the 3D advertisement to obtain association data;
and the display module 13 is configured to collect second facial image information of each customer entering the mall, determine whether each second facial image information is matched with one of the plurality of associated data, and output and display the SD advertisement and store information corresponding to the SD advertisement when matching.
Example three:
referring to fig. 10, this embodiment discloses an embodiment of an electronic device. The electronic device may include a processor 81 and a memory 82 storing computer program instructions.
Specifically, the processor 81 may include a Central Processing Unit (CPU), or A Specific Integrated Circuit (ASIC), or may be configured to implement one or more Integrated circuits of the embodiments of the present Application.
The memory 82 may be used to store or cache various data files for processing and/or communication use, as well as possible computer program instructions executed by the processor 81.
The processor 81 implements any of the mall shopping guide methods in the above embodiments by reading and executing computer program instructions stored in the memory 82.
In some of these embodiments, the electronic device may also include a communication interface 83 and a bus 80. As shown in fig. 10, the processor 81, the memory 82, and the communication interface 83 are connected via the bus 80 to complete mutual communication.
The communication interface 83 is used for implementing communication between modules, devices, units and/or equipment in the embodiment of the present application. The communication port 83 may also be implemented with other components such as: the data communication is carried out among external equipment, image/data acquisition equipment, a database, external storage, an image/data processing workstation and the like.
The bus 80 includes hardware, software, or both to couple the components of the electronic device to one another. Bus 80 includes, but is not limited to, at least one of the following: data Bus (Data Bus), Address Bus (Address Bus), Control Bus (Control Bus), Expansion Bus (Expansion Bus), and Local Bus (Local Bus). By way of example, and not limitation, Bus 80 may include an Accelerated Graphics Port (AGP) or other Graphics Bus, an Enhanced Industry Standard Architecture (EISA) Bus, a Front-Side Bus (FSB), a Hyper Transport (HT) Interconnect, an ISA (ISA) Bus, an InfiniBand (InfiniBand) Interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a microchannel Architecture (MCA) Bus, a PCI (Peripheral Component Interconnect) Bus, a PCI-Express (PCI-X) Bus, a Serial Advanced Technology Attachment (SATA) Bus, a Video Electronics Bus (audio Electronics Association), abbreviated VLB) bus or other suitable bus or a combination of two or more of these. Bus 80 may include one or more buses, where appropriate. Although specific buses are described and shown in the embodiments of the application, any suitable buses or interconnects are contemplated by the application.
The electronic device may be based on mall shopping guide, thereby implementing the mall shopping guide method described in conjunction with fig. 1-3.
In addition, in combination with the shopping guide of the mall in the above embodiment, the embodiment of the present application may be implemented by providing a computer-readable storage medium. The computer readable storage medium having stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement any of the mall shopping guide methods in the above embodiments.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
In conclusion, the advertisement space has the advantages that the problem that the fixed content of the advertisement space is old and the latest product characteristics cannot be accurately displayed for customers is solved; the invention shows the latest popular advertisement products to the customers in a 3D stereo form, thereby realizing the accurate delivery of the advertisements; the system takes the Internet of things as a basis, and actively guides the customers to consume in an all-around manner, and the watch is passively active, so that the situation that the products in the store passively wait for the customers to consume at home before is broken, the latest popular products are actively pushed to the customers, and the customers are guided to accurately consume, and the accurate popularization in the product meaning is realized; the invention is beneficial to the accurate statistical analysis of the advertisement effect.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A shopping guide method for a shopping mall, comprising:
the collection step comprises: acquiring human faces of people watching 3D advertisements outside a business city to obtain a plurality of pieces of first human face image information;
and (3) association step: performing figure drawing on the first face image information by a face recognition technology to obtain a figure drawing corresponding to each first face image information, and associating the figure drawing with advertisement information of the 3D advertisement to obtain associated data;
a display step: and acquiring second face image information of each customer entering the mall, judging whether each second face image information is matched with one of the plurality of associated data, and outputting and displaying the SD advertisement and store information corresponding to the SD advertisement when the second face image information is matched with one of the associated data.
2. The mall shopping guide method according to claim 1, further comprising:
a consumption result information acquisition step: and acquiring third facial image information of a customer entering a store, judging whether the third facial image information is matched with one of the plurality of associated data, and acquiring and storing consumption result information of the customer corresponding to the associated data during matching and then outputting the consumption result information to an information platform of the store.
3. The shopping mall shopping guide method according to claim 2, further comprising:
a step of acquiring statistical information: and binding the consumption result information and the associated data corresponding to the consumption result information to form statistical result information, and outputting the statistical result information to an information platform of the mall.
4. The mall shopping guide method according to claim 1, wherein the associating step comprises:
an advertisement information acquisition step: collecting the advertisement information corresponding to the 3D advertisement;
a figure portrait acquisition step: performing figure drawing on the first face image information by using face features, micro-expression features, time features and task features of the first face image information based on a face recognition technology to obtain the figure drawing;
and a step of acquiring associated data: and associating the character image with the advertisement information to obtain and store the associated data.
5. The mall shopping guide method according to claim 1, wherein the displaying step comprises:
a second face image information acquisition step: collecting the second face image information;
a first judgment step: judging whether each piece of second face image information is matched with one of the associated data or not and outputting a matching result;
an information display step: and when the matching result is consistent, outputting the SD advertisement and the store information.
6. The mall shopping guide method according to claim 5, wherein the store information comprises: and the product information, the store address information and the route information for going to the store corresponding to the SD advertisement.
7. The mall shopping guide method according to claim 6, wherein the displaying step further comprises:
a fourth face image information acquisition step: collecting fourth face image information of the customer traveling along the route information;
a second judgment step: judging whether each fourth face image information is matched with one of the associated data or not and outputting a matching result;
store information display step: and when the matching result is consistent, outputting at least one corresponding one of the product information, the store address information and the route information to at least one display terminal in the commercial city, and playing the store information through the display terminal.
8. A shopping guide system for a mall, comprising:
the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring the faces of people watching 3D advertisements outside a commercial city to obtain a plurality of pieces of first face image information;
the association module is used for performing figure drawing on the first face image information through a face recognition technology to obtain a figure drawing corresponding to each piece of the first face image information, and associating the figure drawing with the advertisement information of the 3D advertisement to obtain association data;
and the display module is used for acquiring second face image information of each customer entering the mall, judging whether each second face image information is matched with one of the plurality of associated data, and outputting and displaying the SD advertisement and store information corresponding to the SD advertisement when the second face image information is matched with one of the associated data.
9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the mall shopping guide method according to any one of claims 1 to 7 when executing the computer program.
10. A storage medium on which a computer program is stored which, when being executed by a processor, carries out a mall shopping guide method according to any one of claims 1 to 7.
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| CN202111282886.XA CN113822726A (en) | 2021-11-01 | 2021-11-01 | Shopping guide method and system for shopping mall, storage medium and electronic equipment |
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| CN202111282886.XA CN113822726A (en) | 2021-11-01 | 2021-11-01 | Shopping guide method and system for shopping mall, storage medium and electronic equipment |
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107730312A (en) * | 2017-09-30 | 2018-02-23 | 广东博媒广告传播有限公司 | A kind of out-of-home media traffic transformation analysis system |
| CN109711900A (en) * | 2018-12-29 | 2019-05-03 | 北京金山安全软件有限公司 | Information display method and device based on face recognition, terminal equipment and storage medium |
| CN109934625A (en) * | 2019-03-01 | 2019-06-25 | 统云信息科技有限公司 | A kind of artificial intelligence display screen advertisement dynamic throwing system and method |
-
2021
- 2021-11-01 CN CN202111282886.XA patent/CN113822726A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107730312A (en) * | 2017-09-30 | 2018-02-23 | 广东博媒广告传播有限公司 | A kind of out-of-home media traffic transformation analysis system |
| CN109711900A (en) * | 2018-12-29 | 2019-05-03 | 北京金山安全软件有限公司 | Information display method and device based on face recognition, terminal equipment and storage medium |
| CN109934625A (en) * | 2019-03-01 | 2019-06-25 | 统云信息科技有限公司 | A kind of artificial intelligence display screen advertisement dynamic throwing system and method |
Non-Patent Citations (1)
| Title |
|---|
| 董安琪: "5G背景下户外广告发展趋势研究", 《经管论坛》, 22 October 2020 (2020-10-22), pages 42 - 43 * |
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