CN111783509A - Automatic settlement method, device, system and storage medium - Google Patents
Automatic settlement method, device, system and storage medium Download PDFInfo
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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
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Abstract
The invention discloses an automatic settlement method, device, system and storage medium, and relates to the technical field of data processing. The automatic settlement method comprises the following steps: identifying a user matched with user image information in the obtained tracking image in the sorting area; determining a first corresponding relation between a user identifier and a coordinate of a user and the acquisition time of a tracking image according to the identified position of the user in the tracking image and the shooting time of the tracking image; identifying a picking image collected by a picking camera positioned in a container to determine picked articles in the picking image; determining a second corresponding relation among the picked and placed articles in the picking image, the coordinates of the picking image acquisition area and the picking image acquisition time; according to the first corresponding relation and the second corresponding relation, the picked and placed items are bound with the user identification of the user located in the picked image acquisition area at the same time; and settling accounts according to the articles bound by the user identification.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to an automatic settlement method, apparatus, system, and storage medium.
Background
In a traditional convenience store, library, etc., people need to reach a settlement place for settlement after purchasing commodities or books for purchase or borrow. In the case of a large number of people, people need to queue up, resulting in a long waiting time.
At present, some scenes identify articles based on Radio Frequency Identification (RFID for short) to realize self-service settlement.
Disclosure of Invention
After the analysis, the inventor finds that the RFID label pasting operation is complex and tedious, the RFID system is high in cost and low in reusability, and therefore the cost of automatic settlement is increased, and the deployment efficiency is reduced.
The embodiment of the invention aims to solve the technical problem that: how to reduce the cost of automatic settlement and improve the deployment efficiency.
According to a first aspect of some embodiments of the present invention, there is provided an automatic settlement method including: acquiring a user identifier and user image information of a corresponding user; identifying a user matched with the user image information in the obtained tracking image in the sorting area, and determining a user identifier of the identified user; determining a first corresponding relation between the user identification and the coordinate of the identified user and the acquisition time of the tracking image according to the position of the identified user in the tracking image and the shooting time of the tracking image; identifying a picking image collected by a picking camera positioned in a container to determine picked articles in the picking image; determining a second corresponding relation among the picked and placed article in the picking image, the coordinates of the picking image acquisition area and the picking image acquisition time according to the coordinates of the picking image acquisition area and the picking image shooting time which are obtained in advance; according to the first corresponding relation and the second corresponding relation, the picked and placed items are bound with the user identification of the user located in the picked image acquisition area at the same time; and settling accounts according to the articles bound by the user identification.
In some embodiments, the picking image is collected in response to a gravity sensor located on the container sensing a change in weight.
In some embodiments, a picking image collected by a picking camera located in a container is gesture-recognized to determine an item being picked and placed in the picking image.
In some embodiments, the automatic settlement method further comprises: identifying a face image of a user collected at an entrance to obtain a corresponding user identifier; after the face image of the user is identified, the first user image information in the tracking image collected from the area adjacent to the entrance in the sorting area corresponds to the user identification.
In some embodiments, the tracking image is acquired by a tracking camera, and the shooting angle of the tracking camera is fixed.
In some embodiments, the automatic settlement method further comprises: and determining the coordinates of the picking image acquisition area according to the position of the picking image acquisition area in the tracking image.
In some embodiments, the tracking image is a video frame.
In some embodiments, settling on items bound by the user identification comprises: collecting an off-field image in a region outside the picking region and adjacent to the outlet; identifying a user matched with the user image information of the user in the user image information in the departure image, and determining that the user corresponding to the corresponding user identification leaves; the items bound by the user identification of the departing user are settled.
According to a second aspect of some embodiments of the present invention, there is provided an automatic settlement apparatus including: the user information acquisition module is configured to acquire a user identifier and user image information of a corresponding user; the user matching module is configured to identify users matched with the user image information in the obtained tracking images in the sorting area and determine user identifications of the identified users; the first corresponding relation determining module is configured to determine a first corresponding relation between the user identification and the coordinate of the identified user and the acquisition time of the tracking image according to the position of the identified user in the tracking image and the shooting time of the tracking image; the goods identification module is configured to identify a picking image shot by a picking camera positioned in the container so as to determine picked goods in the picking image; the second corresponding relation determining module is configured to determine a second corresponding relation among the picked and placed article in the picking image, the coordinates of the picking image collecting area and the picking image collecting time according to the coordinates of the picking image collecting area and the picking image shooting time which are obtained in advance; an item binding module configured to bind the picked and placed item with a user identifier of a user located in the picked image acquisition area at the same time according to the first and second correspondence; and the settlement module is configured to settle the items bound according to the user identification.
According to a third aspect of some embodiments of the present invention, there is provided an automatic settlement apparatus including: a memory; and a processor coupled to the memory, the processor configured to perform any of the foregoing automatic settlement methods based on instructions stored in the memory.
According to a fourth aspect of some embodiments of the present invention, there is provided an automatic settlement system comprising: any one of the above automatic settlement devices; the tracking camera is used for acquiring tracking images or tracking videos comprising the tracking images; and the picking camera is positioned on the container and used for collecting picking images.
In some embodiments, the automated settlement system further comprises: and the face recognition camera is positioned at an entrance of the sorting area and used for collecting a face image of the user.
According to a fifth aspect of some embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements any one of the automatic settlement methods described above.
Some embodiments of the above invention have the following advantages or benefits: embodiments of the present invention may determine the user's location from the tracking images and determine the items being picked and placed from the picking images. And then, determining a user for picking and placing the article according to a matching result of the position of the collection area of the picking image and the position of the user at the same moment so as to realize the association of the user and the article. Therefore, the user can realize the real-time update of the articles to be settled in the process of taking and placing the articles without centralized counting, and the settlement efficiency is improved. In addition, the mode does not need to carry out additional treatment on the articles one by one, and is easy to deploy and low in cost.
Other features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flow diagram of an automated settlement method according to some embodiments of the invention.
FIG. 2 is an exemplary tracking image according to some embodiments of the invention.
FIG. 3 is a flow diagram illustrating a method of user identification as a user enters a picking area in accordance with some embodiments of the invention.
FIG. 4 is a flow diagram of an identification method as a user picks an item, according to some embodiments of the invention.
FIG. 5 is a flow diagram of a settlement method when a user leaves a picking area according to some embodiments of the invention.
Fig. 6 is a schematic diagram of an automatic settlement device according to some embodiments of the present invention.
Fig. 7 is a schematic diagram of an automated settlement system according to some embodiments of the present invention.
Fig. 8 is a schematic deployment diagram of an automated checkout system according to some embodiments of the invention.
Fig. 9 is a schematic structural view of an automatic settlement apparatus according to other embodiments of the present invention.
Fig. 10 is a schematic diagram of an automatic settlement device according to still other embodiments of 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. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses. 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.
The relative arrangement of the components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.
Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
Fig. 1 is a flow diagram of an automated settlement method according to some embodiments of the invention. As shown in fig. 1, the automatic settlement method of this embodiment includes steps S102 to S114.
In step S102, a user identification and user image information of the corresponding user are acquired. The user image information may be the user image itself or an image feature of the user image.
The user image is an image including the whole body or part of the user acquired. The user image information may be, for example, head and shoulder information, face information, clothing information, body shape information, and the like of the user.
In some embodiments, the contour image information may be head-shoulder image information corresponding to the head-shoulder image. The head-shoulder image can be obtained by, for example, performing a downward shot with a camera provided at a high position. The data amount required to be processed in the tracking process can be reduced by using the head and shoulder image information, and the calculation efficiency is improved.
In some embodiments, the correspondence between the user identification and the user image information may be pre-stored in a database, or may be collected after the user enters the picking area. Picking areas may include, for example, enclosed areas such as stores, libraries, etc., where a user may pick and place items and settle.
In step S104, a user matching the user image information is identified in the acquired tracking image within the sorting area, and a user identification of the identified user is determined.
In some embodiments, the tracking image is a video frame. Thus, it is possible to take a video in the picking area and track the same user in the video by analyzing each frame.
In step S106, a first correspondence between the user identification, the coordinates of the identified user, and the acquisition time of the tracking image is determined according to the position of the identified user in the tracking image and the shooting time of the tracking image.
In step S108, the picking image collected by the picking camera located in the container is identified to determine the picked article in the picking image.
In step S110, a second correspondence between the picked-up item in the picking image, the coordinates of the picking image capturing area, and the capturing time of the picking image is determined according to the coordinates of the picking image capturing area and the capturing time of the picking image acquired in advance.
In some embodiments, the picking image is collected in response to a weight sensor located in the same container sensing a weight change. Therefore, the picking camera positioned on the container can collect images only when a user generates picking and placing actions, and energy consumption and system overhead are saved.
The coordinates of the user and the coordinates of the image acquisition area belong to the same coordinate system. In some embodiments, the coordinates of the user and the coordinates of the image acquisition area are located in an image coordinate system of the tracked image. As shown in fig. 2, the upper left corner of the tracking image is assumed to be the origin (0,0) of the image coordinate system of the tracking image acquired at 12:15: 01. By matching the head and shoulder image information of the users U1, U2 in the tracking image, it was determined that the user U1 was located at the point (300,200) and the user U2 was located at the point (100,400) at 12:15: 01. The dashed area in front of shelf S1 is the image capture area of camera C1 on shelf S1. In the pick image captured by camera C1 at 12:15:01, there is an item picked up by a user. Since the center coordinate of the image capturing area of the camera C1 is stored in advance as (301,200), by matching the coordinates of the respective users at 12:15:01, the user U1 is found to be located near the image capturing area of the camera C1 at this time. Thus, it can be determined that the user U1 picked up the item.
In some embodiments, the image coordinate system of the tracking image may also be mapped to other coordinate systems. The coordinates of the user and the coordinates of the image acquisition area are located in the other coordinate system of the map. For example, when a plurality of tracking cameras are used for acquiring tracking images, the image coordinate systems in which the tracking images acquired by different tracking cameras are located may be mapped into a unified coordinate system.
In step S112, according to the first corresponding relationship and the second corresponding relationship, the picked and placed item is bound to the user identifier of the user located in the picked image capturing area at the same time.
In step S114, settlement is performed according to the items bound by the user identification.
By the method of the above embodiment, the position of the user can be determined according to the tracking image, and the picked and placed article can be determined according to the picking image. And then, determining a user for picking and placing the article according to a matching result of the position of the collection area of the picking image and the position of the user at the same moment so as to realize the association of the user and the article. Therefore, the user can realize the real-time update of the articles to be settled in the process of taking and placing the articles without centralized counting, and the settlement efficiency is improved. In addition, the mode does not need to carry out additional treatment on the articles one by one, and is easy to deploy and low in cost.
An embodiment of the identification process when a user enters a picking area is described below with reference to fig. 3.
FIG. 3 is a flow diagram illustrating a method of user identification as a user enters a picking area in accordance with some embodiments of the invention. As shown in fig. 3, the user identification method of this embodiment includes steps S302 to S304.
In step S302, the face image of the user collected at the entrance is recognized to obtain a corresponding user identifier. When the face recognition is carried out, the collected face image of the user can be matched with a face image corresponding to a user identifier stored in a database in advance so as to recognize the identity of the user at the entrance.
In some embodiments, a gate may be provided at the inlet. When the identity of the user is recognized, the gate can be opened for the user to pass through.
In step S304, after the face image of the user is recognized, the first user image information in the tracking image collected from the area adjacent to the entrance in the picking area corresponds to the user identifier.
Upon successful face recognition of the user and the user entering the picking area, a user image may be immediately acquired. The user image collected at this time belongs to the user who just passes the authentication, so the user image information can correspond to the user identification.
The first user image information after the user face image is identified refers to the user image information of the first user appearing in the region adjacent to the entrance in the sorting region after the user face image is identified. Thus, the user identification can be accurately corresponded to the user image.
By the method of the above embodiment, the user image information of the user in the sorting area can be accurately determined.
An embodiment of an identification process when a user picks an item is described below with reference to fig. 4.
FIG. 4 is a flow diagram of an identification method as a user picks an item, according to some embodiments of the invention. As shown in fig. 4, the identification method of this embodiment includes steps S402 to S406.
In step S402, in response to the gravity sensor located in the container sensing a weight change, a photographing instruction is transmitted to the camera located in the same container. This shoot instruction can be directly sent for the camera by gravity sensor direct through modes such as wireless network, bluetooth, signal of telecommunication, also can be fed back to the server through the network by gravity sensor, again will shoot the instruction and send for the camera through the network by the server, can also monitor gravity sensor's weight value by the server, and will shoot the instruction and send for the camera through the network when the weight value of monitoring changes.
In step S404, the cameras located in the same container perform photographing in response to the photographing instruction, and a picked-up image is obtained.
In step S406, gesture recognition is performed on the picked image captured by the camera, and the picked article in the picked image is determined.
Because the shooting angle of the camera placed on the container is relatively fixed, when a user takes and places articles on the shelf, the actions and angles of the hand and the arm are similar. Thus, it is possible to identify which items are the items taken and placed by the user.
An embodiment of the settlement flow when the user leaves the picking area is described below with reference to fig. 5.
FIG. 5 is a flow diagram of a settlement method when a user leaves a picking area according to some embodiments of the invention. As shown in fig. 5, the settlement method of this embodiment includes steps S502 to S506.
In step S502, an off-field image is acquired in a region adjacent to the exit outside the sorting region.
In some embodiments, the user triggers the gate to open by infrared sensing or a manual button after picking the item and before exiting the gate. In response to the gate opening, a camera located outside the exit may capture an off-field image.
In step S504, a user matching the user image information of the user is identified in the user image information in the outlier image, and it is determined that the user corresponding to the corresponding user identifier leaves.
In step S506, the items bound by the user identification of the departing user are settled. For example, the amount corresponding to the article bound by the user identifier is calculated, and a deduction is made in an account corresponding to the user identifier; or recording the items bound by the user identification into the use list and the borrowing list of the user.
By the method of the above embodiment, the settlement operation can be triggered by the departure of the user.
An embodiment of the automatic settlement apparatus of the present invention is described below with reference to fig. 6.
Fig. 6 is a schematic diagram of an automatic settlement device according to some embodiments of the present invention. As shown in fig. 6, the automatic settlement apparatus 600 of this embodiment includes: a user information obtaining module 6100 configured to obtain a user identification and user image information of a corresponding user; a user matching module 6200 configured to identify a user matching the user image information in the obtained tracked image within the picking area and determine a user identification of the identified user; a first correspondence determining module 6300 configured to determine a first correspondence between the user identifier of the identified user, the coordinates, and the acquisition time of the tracking image according to the position of the identified user in the tracking image and the shooting time of the tracking image; an item identification module 6400 configured to identify a picking image captured by a picking camera located in the container to determine an item picked in the picking image; a second correspondence determining module 6500 configured to determine, according to coordinates of a picking image acquisition area and shooting time of the picking image acquired in advance, a second correspondence between an item taken and placed in the picking image, coordinates of the picking image acquisition area, and acquisition time of the picking image; an item binding module 6600 configured to bind the picked and placed item with a user identifier of a user located within the picked image capture area at the same time according to the first and second correspondence; a settlement module 6700 configured to settle according to the items bound by the user identification.
In some embodiments, the picking image is collected in response to a gravity sensor located on the container sensing a change in weight.
In some embodiments, the item identification module 6400 is further configured to gesture recognize picking images collected by picking cameras located in the container to determine picked items in the picking images.
In some embodiments, the automatic settlement apparatus 600 further includes: the face recognition module 6800 is configured to recognize a face image of the user collected at the entrance to obtain a corresponding user identifier; after the face image of the user is identified, the first user image information in the tracking image collected from the area adjacent to the entrance in the sorting area corresponds to the user identification.
In some embodiments, the tracking image is acquired by a tracking camera, and the shooting angle of the tracking camera is fixed.
In some embodiments, the automatic settlement apparatus 600 further includes: a picking image acquisition area coordinate determination module 6900 configured to determine coordinates of a picking image acquisition area according to a position of the picking image acquisition area in the tracking image.
In some embodiments, the tracking image is a video frame.
In some embodiments, the settlement module 6700 is further configured to acquire departure images in areas outside the picking area adjacent to the exit; identifying a user matched with the user image information of the user in the user image information in the departure image, and determining that the user corresponding to the corresponding user identification leaves; the items bound by the user identification of the departing user are settled.
An embodiment of the automatic settlement system of the present invention is described below with reference to fig. 7 and 8.
Fig. 7 is a schematic diagram of an automated settlement system according to some embodiments of the present invention. As shown in fig. 7, the automatic settlement system 70 of this embodiment includes: an automatic settlement device 710, the specific implementation of which can refer to the automatic settlement device 600 in the embodiment of fig. 6; a tracking camera 720 for acquiring a tracking image or a tracking video including the tracking image; and a picking camera 730 located in the container for collecting picking images.
In some embodiments, the automated settlement system 70 further comprises: and the face recognition camera 740 is positioned at an entrance of the sorting area and is used for collecting a face image of the user.
Fig. 8 is a schematic deployment diagram of an automated checkout system according to some embodiments of the present invention, wherein the diagram illustrates a top view of a self-service supermarket.
In the scene 80, a face recognition camera 81 is provided at an entrance 801. The face recognition camera 81 acquires a face image and transmits the face image to a server (not shown) for recognition, wherein an automatic settlement device is disposed on the server. And the server determines the user identification according to the face image. After the user completes face recognition at the entry 801, the user walks into the supermarket along the entry way 802. The portal tracking camera 82 at the top of the portal channel 802 captures the user's image and transmits it to the server so that the server can determine the correspondence between the user identification and the user's image information.
When the user is in the supermarket, the tracking camera 83 arranged at the top of the supermarket collects the user image of the user so as to realize the tracking and positioning of the user. When a user picks up an item in front of a shelf 803, a picking camera 84 located on the same shelf collects a picking image and transmits it to a server in response to a weight sensor on the shelf 803 detecting a weight change. The server identifies the picked item in the picking image and corresponding location information. And the server determines which user takes the article by matching the position of the user and the position of the taken and placed article so as to bind the user identification and the corresponding article.
When the user is ready to leave the supermarket, the tracking camera 85 positioned in the exit passage collects the user image of the user and sends the user image to the server, and the server confirms that the corresponding user leaves and settles the items bound by the user.
Fig. 9 is a schematic structural view of an automatic settlement apparatus according to other embodiments of the present invention. As shown in fig. 9, the automatic settlement apparatus 90 of this embodiment includes: a memory 910 and a processor 920 coupled to the memory 910, the processor 920 being configured to perform the automatic settlement method in any of the embodiments described above based on instructions stored in the memory 910.
Fig. 10 is a schematic diagram of an automatic settlement device according to still other embodiments of the present invention. As shown in fig. 10, the automatic settlement apparatus 100 of this embodiment includes: the memory 1010 and the processor 1020 may further include an input/output interface 1030, a network interface 1040, a storage interface 1050, and the like. These interfaces 1030, 1040, 1050 and the memory 1010 and the processor 1020 may be connected via a bus 1060, for example. The input/output interface 1030 provides a connection interface for input/output devices such as a display, a mouse, a keyboard, and a touch screen. Network interface 1040 provides a connection interface for various networking devices. The storage interface 1050 provides a connection interface for external storage devices such as an SD card and a usb disk.
An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is configured to implement any one of the automatic settlement methods when executed by a processor.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (13)
1. An automatic settlement method comprising:
acquiring a user identifier and user image information of a corresponding user;
identifying a user matched with the user image information in the obtained tracking image in the sorting area, and determining a user identifier of the identified user;
determining a first corresponding relation between the user identification and the coordinate of the identified user and the acquisition time of the tracking image according to the position of the identified user in the tracking image and the shooting time of the tracking image;
identifying a picking image collected by a picking camera positioned in a container to determine picked articles in the picking image;
determining a second corresponding relation among the picked and placed article in the picking image, the coordinates of the picking image acquisition area and the picking image acquisition time according to the coordinates of the picking image acquisition area and the picking image shooting time which are obtained in advance;
according to the first corresponding relation and the second corresponding relation, the picked and placed article and the user identification of the user located in the picking image acquisition area at the same time are bound;
and settling accounts according to the articles bound by the user identification.
2. The automatic settlement method of claim 1 wherein the picking image is collected in response to a weight change sensed by a gravity sensor located at the container.
3. The automatic settlement method according to claim 1, wherein gesture recognition is performed on picking images collected by picking cameras located in containers to determine picked items in the picking images.
4. The automatic settlement method according to claim 1, further comprising:
identifying a face image of a user collected at an entrance to obtain a corresponding user identifier;
and after the face image of the user is identified, corresponding first user image information in a tracking image collected from an area adjacent to the entrance in the sorting area to the user identification.
5. The automatic settlement method according to claim 1, wherein the tracking image is collected by a tracking camera whose shooting angle is fixed.
6. The automatic settlement method according to claim 5, further comprising:
and determining the coordinates of the picking image acquisition area according to the position of the picking image acquisition area in the tracking image.
7. The automatic settlement method of claim 1, wherein the tracking image is a video frame.
8. The automatic settlement method of claim 1, wherein said settling the items bound according to the user identification comprises:
collecting an off-field image in a region outside the picking region and adjacent to the outlet;
identifying a user matched with the user image information of the user in the user image information in the departure image, and determining that the user corresponding to the corresponding user identification leaves;
the items bound by the user identification of the departing user are settled.
9. An automatic settlement device comprising:
the user information acquisition module is configured to acquire a user identifier and user image information of a corresponding user;
a user matching module configured to identify a user matching the user image information in the acquired tracking image within the sorting area and determine a user identification of the identified user;
the first corresponding relation determining module is configured to determine a first corresponding relation between the user identification and the coordinate of the identified user and the acquisition time of the tracking image according to the position of the identified user in the tracking image and the shooting time of the tracking image;
the goods identification module is configured to identify a picking image shot by a picking camera positioned in the container so as to determine picked goods in the picking image;
the second corresponding relation determining module is configured to determine a second corresponding relation among the picked and placed article in the picking image, the coordinates of the picking image collecting area and the picking image collecting time according to the coordinates of the picking image collecting area and the picking image shooting time which are obtained in advance;
an item binding module configured to bind the picked and placed item with a user identifier of a user located in the picked image acquisition area at the same time according to the first and second correspondence;
and the settlement module is configured to settle the items bound according to the user identification.
10. An automatic settlement device comprising:
a memory; and
a processor coupled to the memory, the processor configured to perform the automated settlement method of any of claims 1-8 based on instructions stored in the memory.
11. An automatic settlement system comprising:
the automatic settlement device of claim 9 or 10;
the tracking camera is used for acquiring tracking images or tracking videos comprising the tracking images; and
the picking camera is positioned on the container and used for collecting picking images.
12. The automatic settlement system of claim 11, further comprising:
and the face recognition camera is positioned at an entrance of the sorting area and used for collecting a face image of the user.
13. A computer-readable storage medium on which a computer program is stored, which when executed by a processor implements the automatic settlement method of any one of claims 1 to 8.
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| CN201910807464.6A CN111783509A (en) | 2019-08-29 | 2019-08-29 | Automatic settlement method, device, system and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112416961A (en) * | 2020-11-19 | 2021-02-26 | 北京爱笔科技有限公司 | Method and device for confirming association relationship between people and goods |
| CN116708801A (en) * | 2023-08-04 | 2023-09-05 | 广东星云开物科技股份有限公司 | Video compression method, shared sales counter and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108198052A (en) * | 2018-03-02 | 2018-06-22 | 北京京东尚科信息技术有限公司 | User's free choice of goods recognition methods, device and intelligent commodity shelf system |
| CN108268134A (en) * | 2017-12-30 | 2018-07-10 | 广州本元信息科技有限公司 | The gesture identifying device and method of taking and placing commodity |
| CN108332829A (en) * | 2017-12-18 | 2018-07-27 | 上海云拿智能科技有限公司 | Kinds of goods sensory perceptual system based on monitoring weight and kinds of goods cognitive method |
| CN109447756A (en) * | 2018-10-31 | 2019-03-08 | 李义 | A kind of unattended supermarket shopping method and system |
-
2019
- 2019-08-29 CN CN201910807464.6A patent/CN111783509A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108332829A (en) * | 2017-12-18 | 2018-07-27 | 上海云拿智能科技有限公司 | Kinds of goods sensory perceptual system based on monitoring weight and kinds of goods cognitive method |
| CN108268134A (en) * | 2017-12-30 | 2018-07-10 | 广州本元信息科技有限公司 | The gesture identifying device and method of taking and placing commodity |
| CN108198052A (en) * | 2018-03-02 | 2018-06-22 | 北京京东尚科信息技术有限公司 | User's free choice of goods recognition methods, device and intelligent commodity shelf system |
| CN109447756A (en) * | 2018-10-31 | 2019-03-08 | 李义 | A kind of unattended supermarket shopping method and system |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112416961A (en) * | 2020-11-19 | 2021-02-26 | 北京爱笔科技有限公司 | Method and device for confirming association relationship between people and goods |
| CN112416961B (en) * | 2020-11-19 | 2024-03-12 | 北京爱笔科技有限公司 | Method and device for confirming association relationship of people and goods |
| CN116708801A (en) * | 2023-08-04 | 2023-09-05 | 广东星云开物科技股份有限公司 | Video compression method, shared sales counter and storage medium |
| CN116708801B (en) * | 2023-08-04 | 2023-11-03 | 广东星云开物科技股份有限公司 | Video compression method, shared sales counter and storage medium |
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