Three-dimensional modeling method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention relates to a three-dimensional modeling method and device, equipment, a storage medium and a program product. The method comprises the following steps: determining entity attribute information of a plurality of entities and label position information corresponding to labels respectively pasted on the plurality of entities; grouping the plurality of entities based on the first label position information to obtain a plurality of first entity groups; in each first entity group, based on the second label position information of the entities in each first entity group, grouping the entities in each first entity group to obtain a plurality of second entity groups; and creating three-dimensional models corresponding to the plurality of entities based on the plurality of second entity groups, the entity attribute information and the label position information corresponding to each entity in the plurality of second entity groups. According to the method, on the premise that the accuracy of three-dimensional modeling is guaranteed, the modeling efficiency of three-dimensional modeling can be improved, and computing resources consumed by three-dimensional modeling are saved.

Description

Technical Field

[0001] Example embodiments of the present disclosure generally relate to the field of computer technology, and more particularly, to a method, apparatus, electronic device, computer-readable storage medium, and computer program product for three-dimensional modeling. Background Art

[0002] With the advancement of digital twin technology, more and more applications and platforms are beginning to use 3D modeling to reproduce real scenes. By simulating and optimizing simulations in these virtual environments, the performance and efficiency of actual scenes can be effectively improved and enhanced, bringing many conveniences to applications, platforms, and users. To ensure the accuracy of 3D models, it is usually necessary to collect a large amount of data from real scenes and use this data to build 3D models in virtual environments. It is expected that the resource consumption of 3D modeling can be reduced while ensuring the accuracy of modeling. Summary of the invention

[0003] In the first aspect of the present disclosure, a method for three-dimensional modeling is provided. The method includes: determining entity attribute information of multiple entities and label position information corresponding to labels respectively attached to the multiple entities, the label position information includes first label position information and second label position information, the first label position information and the second label position information indicate the position information of the corresponding entity in different directions; based on the first label position information, the multiple entities are grouped to obtain multiple first entity groups, each of which includes at least one entity among the multiple entities; in each first entity group, based on the second label position information of the entities in each first entity group, the entities in each first entity group are grouped to obtain multiple second entity groups, each of which includes at least one entity in the first entity group; and based on the multiple second entity groups, the entity attribute information, and the label position information corresponding to each entity in the multiple second entity groups, create three-dimensional models corresponding to each of the multiple entities.

[0004] In the second aspect of the present disclosure, a device for three-dimensional modeling is provided. The device includes: an information determination module, configured to determine entity attribute information of multiple entities and label position information corresponding to labels respectively attached to the multiple entities, the label position information includes first label position information and second label position information, the first label position information and the second label position information represent the position information of the corresponding entity in different directions; a first grouping module, configured to group the multiple entities based on the first label position information to obtain multiple first entity groups, each of which includes at least one entity among the multiple entities; a second group determination module, configured to group the entities in each first entity group based on the second label position information of the entities in each first entity group, to obtain multiple second entity groups, each of which includes at least one entity in the first entity group; and a modeling module, configured to create three-dimensional models corresponding to each of the multiple entities based on the multiple second entity groups, the entity attribute information, and the label position information corresponding to each entity in the multiple second entity groups.

[0005] In a third aspect of the present disclosure, an electronic device is provided. The device includes at least one processing unit; and at least one memory, the at least one memory is coupled to the at least one processing unit and stores instructions for execution by the at least one processing unit. When the instructions are executed by the at least one processing unit, the electronic device executes the method of the first aspect.

[0006] In a fourth aspect of the present disclosure, a computer-readable storage medium is provided, wherein a computer program is stored on the medium, and when the computer program is executed by a processor, the method of the first aspect is implemented.

[0007] In a fifth aspect of the present disclosure, a computer program product is provided, which includes a computer program, wherein when the computer program is executed by a processor, the method according to the first aspect of the present disclosure is implemented.

[0008] It should be understood that the content described in this section is not intended to limit the key features or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In the following, in conjunction with the accompanying drawings and with reference to the following detailed description, the above and other features, advantages and aspects of various implementations of the present disclosure will become more apparent. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0010] Figure 1 A schematic diagram showing an example environment in which embodiments of the present disclosure can be implemented;

[0011] Figure 2 A flowchart showing a process of three-dimensional modeling according to some embodiments of the present disclosure;

[0012] Figure 3A A schematic top view of a shelf arrangement according to some embodiments of the present disclosure is shown;

[0013] Figure 3B A schematic top view of a shelf arrangement grouping according to some embodiments of the present disclosure is shown;

[0014] Figure 4 A schematic top view of a rack intersection according to some embodiments of the present disclosure is shown;

[0015] Figure 5 A schematic top view of the shelf aisle grouping according to some embodiments of the present disclosure is shown;

[0016] Figure 6 A schematic diagram showing a process of aisle grouping within shelf grouping according to some embodiments of the present disclosure;

[0017] Fig. 7A A schematic top view of shelf blocking in a shelf blocking scenario according to some embodiments of the present disclosure is shown;

[0018] Figure 7B A schematic top view of shelf overlap in a shelf blocking scenario according to some embodiments of the present disclosure is shown;

[0019] Figure 7C A schematic top view of shelf separation results in a shelf blocking scenario according to some embodiments of the present disclosure is shown;

[0020] Figure 8 A schematic structural block diagram of an apparatus for three-dimensional modeling according to some embodiments of the present disclosure is shown; and

[0021] Fig. 9 A block diagram of a computing device is shown in which one or more embodiments of the present disclosure may be implemented. DETAILED DESCRIPTION

[0022] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0023] In the description of the embodiments of the present disclosure, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". Other explicit and implicit definitions may also be included below.

[0024] It should be noted that the acquisition, storage and application of user personal information involved in the technical solution of the present disclosure are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0025] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0026] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information, so that the user can independently choose whether to provide personal information to software or hardware such as electronic devices, applications, servers or storage media that execute operations of the technical solution of the present disclosure based on the prompt message.

[0027] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information is sent to the user in a manner such as a pop-up window, in which the prompt information can be presented in text form. In addition, the pop-up window can also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0028] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation to the embodiments of the present disclosure. Other methods that meet relevant laws and regulations may also be applied to the embodiments of the present disclosure.

[0029] As used in this article, the term "point cloud model" is also called PointCloud, which is a geometric model used to represent three-dimensional spatial data. It consists of a set of points in three-dimensional space, and each point contains the position information of the point in three-dimensional space, such as coordinate information. The point cloud clusters formed by clustering based on the point cloud model can calculate the position information of objects in three-dimensional space.

[0030] "Visual Simultaneous Localization and Mapping" is also known as vSLAM (Visual Simultaneous Localization and Mapping), which is a technology that uses visual sensors such as cameras or depth cameras to model and navigate real environments. "Visual Simultaneous Localization and Mapping" combines the two key tasks of simultaneous positioning (SLAM) and mapping (Mapping). It can achieve positioning and navigation of devices such as robots or drones by analyzing visual information in the environment without positioning information or other sensor assistance.

[0031] Generally, three-dimensional modeling of real scenes can be achieved by scanning the scene structure, object position information, etc. in the real scene. For ease of understanding, the present disclosure takes the warehouse digital twin scene as an example for illustrative explanation, but is not limited to this. For example, the present disclosure can also perform three-dimensional modeling of interior decoration scenes, which will not be elaborated herein.

[0032] In the warehouse digital twin scenario, the warehouse structure can usually be scanned, and calculations can be performed after the scan to obtain the size, position, and posture characteristics of the shelves in the warehouse scene (such as the front and back of the shelves, the direction of shelf arrangement, etc.).

[0033] For example, laser scanning can be used to form a point cloud model, which can be clustered to form point cloud clusters, and then the point cloud clusters can be inferred to obtain shelf information such as the size, position, and posture characteristics of the shelf. For another example, a panoramic camera can be used to generate a panoramic video, parse a panoramic photo, and then based on the visual synchronous positioning and map construction technology, the size, position, posture characteristics of the shelf and other shelf information can be comprehensively calculated.

[0034] Furthermore, based on shelf information such as shelf size, location, and posture features, three-dimensional modeling of the warehousing scene can be achieved.

[0035] Figure 1 1 is a schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented. Figure 1 As shown, the example environment 100 may include an electronic device 110. The electronic device 110 may be configured to generate a corresponding three-dimensional model based on the acquired shelf information (eg, the size, position, and posture characteristics of the shelf, etc.).

[0036] The electronic device 110 may include any computing system with computing capabilities, such as various computing devices / systems, terminal devices, server devices, etc. The terminal device may be any type of mobile terminal, fixed terminal or portable terminal, including a mobile phone, a desktop computer, a laptop computer, a notebook computer, a netbook computer, a tablet computer, a media computer, a multimedia tablet, a handheld computer, a portable game terminal, a VR / AR device, a personal communication system (PCS) device, a personal navigation device, a personal digital assistant (PDA), an audio / video player, a digital camera / camcorder, a positioning device, a television receiver, a radio broadcast receiver, an e-book device, a game device, or any combination of the foregoing, including accessories and peripherals of these devices or any combination thereof.

[0037] The server-side device can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks, and big data and artificial intelligence platforms. Server-side devices can include computing systems / servers such as mainframes, edge computing nodes, computing devices in cloud environments, and so on.

[0038] It should be understood that the structure and function of the various elements in the environment 100 are described for exemplary purposes only and do not imply any limitation on the scope of the present disclosure.

[0039] As briefly mentioned above, in order to achieve 3D modeling of the storage environment, that is, 3D modeling of the shelves, it is necessary to collect a large amount of physical information in the real storage environment through various data acquisition devices such as laser scanning and panoramic cameras. Since the collected physical information is usually more complex, such as point cloud models, panoramic videos, etc., it is necessary to use more complex computer algorithms to obtain the location information of the shelves. In other words, obtaining the location information of the shelves usually requires a large amount of physical and computing resources.

[0040] Moreover, the physical information in the storage environment obtained by data acquisition equipment cannot be directly analyzed to obtain the posture characteristics of the shelves (such as the front and back of the shelves, the arrangement direction of the shelves, etc.). The collected physical information needs to be manually marked to represent the posture characteristics of the shelves. Manual marking is time-consuming and labor-intensive, which seriously affects the modeling speed and modeling cost of the three-dimensional modeling of the warehouse digital twin scene.

[0041] In view of this, an embodiment of the present disclosure provides an improved solution for three-dimensional modeling. In this solution, entity attribute information of multiple entities and label position information corresponding to labels respectively attached to the multiple entities are determined, and the label position information includes first label position information and second label position information, and the first label position information and the second label position information indicate the position information of the corresponding entity in different directions. Based on the first label position information, the multiple entities are grouped to obtain multiple first entity groups, and each first entity group includes at least one entity among the multiple entities. In each first entity group, based on the second label position information of the entities in each first entity group, the entities in each first entity group are grouped to obtain multiple second entity groups, and each second entity group includes at least one entity in the first entity group; and based on the multiple second entity groups, the entity attribute information, and the label position information corresponding to each entity in the multiple second entity groups, create three-dimensional models corresponding to each of the multiple entities.

[0042] In this way, the three-dimensional models corresponding to multiple entities (such as shelves) can be established without acquiring a large amount of data through acquisition equipment and without manual labeling. Using such a three-dimensional modeling method to create three-dimensional models corresponding to multiple entities can reduce computing resources and computing costs and increase computing speed.

[0043] Some example embodiments of the present disclosure will be described below with continued reference to the accompanying drawings.

[0044] Figure 2 1 shows a flowchart of a process 200 of three-dimensional modeling according to some embodiments of the present disclosure. The process 200 may be implemented at the electronic device 110. For ease of discussion, reference will be made to Figure 1 The process 200 is described with reference to the environment 100 of FIG.

[0045] At box 210, the electronic device 110 determines entity attribute information of multiple entities and label position information corresponding to labels attached to each of the multiple entities, the label position information includes first label position information and second label position information, the first label position information and the second label position information indicate the position information of the corresponding entity in different directions. Entities are objects in real scenes, such as the above-mentioned shelves. In some embodiments, the three-dimensional modeling process of the present disclosure is mainly used to quickly and with low computational cost generate a three-dimensional model corresponding to an entity based on entity attribute information and label position information corresponding to labels attached to the entity.

[0046] In some embodiments, the entity attribute information may include entity shape, entity size, etc., and may also include any other appropriate type of features that can be used to create a three-dimensional model. In some embodiments, the entity attribute information may be set by a user, or obtained from a third-party application or platform, or randomly generated by a computer using some algorithms, tools, machine learning models, etc., and the present disclosure does not limit this.

[0047] In some embodiments, the label is a physical label attached to an entity, including but not limited to a barcode label, a QR code label, an electronic label, etc. The label position information can be understood as the position information of the label relative to the storage environment, including but not limited to the horizontal position information, the vertical position information, the height position information, etc. Since the label is attached to the entity, based on the horizontal position information, the vertical position information, etc. of the label, the horizontal position information, the vertical position information, etc. of the entity to which the label is attached can be determined.

[0048] In some embodiments, the method of acquiring tag location information includes but is not limited to collecting signals from electronic tags, taking photos to identify tags in a storage environment, etc., and the present disclosure does not limit this.

[0049] In some embodiments, multiple entities may be arranged side by side horizontally or side by side vertically. Taking the entity as a shelf as an example, the entity label is a shelf label, such as a label attached to a storage location of the shelf.

[0050] For example, Figure 3A 3A shows a schematic top view of a shelf arrangement according to some embodiments of the present disclosure. For example, Figure 3A In the example, frame 310 includes six shelves, which are arranged closely in three rows and two columns. Closely means that there is no passage between the shelves. As shown in frame 310, there is no passage between the first column and the second column, and there is no passage between the first row, the second row, and the third row. The longitudinal length of each shelf is greater than the transverse length, which is a longitudinal arrangement. Similarly, frame 330 has a row of three columns of closely adjacent shelves arranged transversely, and frame 320 has two rows and three columns of closely adjacent shelves arranged transversely.

[0051] Since the dimensions of the horizontally arranged shelves and the vertically arranged shelves in the same direction are inconsistent, Figure 3A Analyzing the label location information of the shelves shown will result in a large consumption of resources.

[0052] In some embodiments, the multiple entities may be multiple entities with the same arrangement direction. Based on this, the multiple entities can be obtained from the multiple initial entities by screening based on the arrangement direction. Specifically, the multiple initial entities and the initial label position information corresponding to the labels respectively attached to the multiple initial entities are determined; the arrangement direction of the multiple initial entities is determined based on the initial label position information corresponding to the labels respectively attached to the multiple initial entities; and the multiple entities are determined from the multiple initial entities based on the arrangement direction of the multiple initial entities and the predetermined arrangement direction requirements. The multiple initial entities are such as the above Figure 3A For all entities in the method, the predetermined arrangement direction is required to be horizontal or vertical, etc., and entities in the multiple initial entities that are consistent with the predetermined arrangement direction are taken as multiple entities.

[0053] For example, Figure 3B As shown, Figure 3B A schematic top view of a shelf arrangement grouping according to some embodiments of the present disclosure is shown. Figure 3B In the figure, the entities included in the frame 340 are entities arranged in the horizontal direction, and the entities included in the frame 350 are entities arranged in the vertical direction.

[0054] In some embodiments, the multiple initial entities may be further divided into entity groups arranged horizontally and entity groups arranged vertically, and modeled separately.

[0055] In some embodiments, the arrangement direction of multiple entities can be determined based on the degree of horizontal or vertical difference between labels affixed to the multiple entities. For example, if the entities corresponding to multiple labels whose horizontal differences are within a preset difference threshold range have a vertical difference greater than the preset difference threshold and less than the lane width, then the multiple entities are arranged horizontally.

[0056] In some embodiments, the first label position information represents the position information of the entity in the first direction, where the first direction is, for example, horizontal, vertical, etc., that is, the position information of the entity in the first direction is reflected by the first label position information of the label pasted on the entity. Based on this, the first label position information can be used to determine whether there is a vacant area between multiple entities in the first direction. For example, when the entity is a shelf, it can be determined whether there is an aisle between multiple shelves.

[0057] As some examples, the shelves may not be aligned. To improve modeling accuracy, they may be divided into aisles from all directions.

[0058] For example, see Figure 4 , Figure 4 A schematic top view of a rack intersection according to some embodiments of the present disclosure is shown. Figure 4There is a horizontal lane between the shelf grouping shown in the middle frame 410-1 and the shelf grouping shown in the frame 410-2, and the shelf grouping shown in the frame 410-3 intersects with the horizontal lane. In this case, the shelf grouping is performed with the first direction as the horizontal direction, and the division of the shelf grouping shown in the frame 410-1 and the shelf grouping shown in the frame 410-2 will be interfered by the shelf grouping shown in the frame 410-3.

[0059] Back to Figure 2 At box 220, the electronic device 110 groups the multiple entities based on the first tag location information to obtain multiple first entity groups, each of which includes at least one entity from the multiple entities.

[0060] In some embodiments, based on the position information of the corresponding entities in the first direction indicated by the first tag position information of the multiple entities, first position difference information between the multiple entities in the first direction is determined; and based on the first position difference information, the multiple entities are grouped to obtain multiple first entity groups, and the first position difference information between any two entities in any entity group meets the predetermined first position difference requirement.

[0061] As some examples, the first position difference information between two entities can be understood as the position difference of the first tag position information of the tags corresponding to the two entities in the first direction. For example, when the tag position is represented by coordinates, the position difference can be understood as the coordinate difference.

[0062] The predetermined first position difference requirement can be understood as being smaller than the preset lane width, that is, if the position difference of the first label information of the labels corresponding to the two entities in the first direction is smaller than the preset lane width, the two entities can be considered to be entities of the same group and there is no lane between the two entities.

[0063] like Figure 5 As shown, Figure 5 A schematic top view of shelf-aisle groupings according to some embodiments of the present disclosure is shown. Figure 5 Taking the first direction as the longitudinal direction as an example, the shelves are grouped longitudinally. The shelf groups (i.e., first entity groups) shown in boxes 510-1, 510-2, and 510-3 have no lanes between the internal shelves (within the first entity group), and there are lanes between shelves in different boxes (between different first entity groups).

[0064] Back to Figure 2 At box 230, the electronic device 110 groups the entities in each first entity group based on the second tag position information of the entities in each first entity group to obtain multiple second entity groups, each second entity group including at least one entity in the first entity group.

[0065] As some examples, the second tag position information is, for example, horizontal, that is, in each first entity group, the entities are grouped in the horizontal direction.

[0066] In some embodiments, each first entity group is determined as a target first entity group in turn; based on the second tag position information of the entity in the target first entity group, the entities in the target first entity group are grouped to obtain multiple sub-entity groups corresponding to the target first entity group; and based on the multiple sub-entity groups corresponding to the target first entity group, multiple second entity groups are obtained.

[0067] In some embodiments, based on the position information of the corresponding entity in the second direction indicated by the second label position information of the entity in the target first entity group, each entity in the target first entity group is sorted to obtain an entity sorting result corresponding to the target first entity group; and based on the entity sorting result and the position information of the corresponding entity in the second direction indicated by the second label position information of the entity in the target first entity group, the entities in the target first entity group are grouped to obtain multiple sub-entity groups corresponding to the target first entity group.

[0068] In some embodiments, based on the entity sorting result, the first entity is determined as the target entity from the target first entity group; the target group queue is determined, and the target entity is marked in the target group queue; based on the entity sorting result, the next entity of the target entity is determined from the target first entity group, and based on the second label information of the target entity and the second label information of the next entity, the second position difference information in the second direction between the target entity and the next entity is determined; it is judged whether the second information difference information meets the preset second position difference requirement, if so, the next entity is marked in the group queue, and the next entity is determined as the target entity, and the step of determining the next entity of the target entity from the target first entity group is continued until there is no next entity of the target entity, if not, a new target group queue is created, the next entity is determined as the target entity, and the step of determining the next entity of the target entity from the target first entity group is continued until there is no next entity of the target entity; and based on the entities marked in each target group queue, the entities in the target first entity group are grouped.

[0069] by Figure 6 For example, the above steps are explained exemplarily. Figure 6 , Figure 6 A schematic diagram of the process of aisle grouping within shelf grouping according to some embodiments of the present disclosure is shown.

[0070] exist Figure 6In the example, the first entity group includes entity 610-1, entity 610-2, entity 610-3, entity 610-4, entity 610-5, entity 610-6, and entity 610-7. The entities in the first entity group are sorted based on the horizontal position, and the sorting result is entity 610-1, entity 610-2, entity 610-3, entity 610-4, entity 610-5, entity 610-6, and entity 610-7. The target group queue is determined, and entity 610-1 is marked to the group queue.

[0071] The lateral position difference (i.e., the second position difference) between entity 610-1 and entity 610-2 is less than the predetermined lane width, i.e., it meets the predetermined second position difference requirement. It is considered that entity 610-1 and entity 610-2 are entities in the same second entity group, and entity 610-2 is marked to the target group queue, i.e., the target group queue where entity 610-1 is located.

[0072] Continuing to compare the lateral position difference (i.e., the second position difference) between entity 610-2 and entity 610-3, it is less than the predetermined lane width, that is, the predetermined second position difference requirement is met, and entity 610-3 and entity 610-2 are considered to be entities in the same second entity group, and entity 610-3 is also marked to the target group queue, that is, the target group queue where entity 610-1 and entity 610-2 are located.

[0073] And so on, the entity 610 - 3 , the entity 610 - 4 , and the entity 610 - 5 are marked to the target packet queue.

[0074] Continuing to compare the lateral position difference (i.e., the second position difference) between entity 610-5 and entity 610-6 is greater than the predetermined lane width, that is, the predetermined second position difference requirement is not met. It is considered that entity 610-6 and entity 610-5 are entities in different second entity groups, a new target group queue is created, and entity 610-6 is marked to the newly created target group queue.

[0075] Similarly, entity 610-7 and entity 610-6 are marked in the same target group queue, based on which two second entity groups are obtained, (610-1, entity 610-2, entity 610-3, entity 610-4, entity 610-5) and (entity 610-6, entity 610-7).

[0076] In some embodiments, there is a situation of lane obstruction, e.g. Fig. 7A As shown, entity 710 - 1 should be an aisle, but due to various factors, such as unreasonable shelf placement, label recognition errors, etc., entity 710 - 1 is displayed as a solid.

[0077] Based on this, the next entity can be marked in the group queue, and the next entity can be determined as the target entity; based on the second tag position information of the target entity, multiple overlapping entities corresponding to the target entity are determined from multiple entities, and the second position difference between the multiple overlapping entities and the target entity in the second direction meets the predetermined overlapping position difference requirement; and it is determined whether the number of multiple overlapping entities meets the predetermined overlapping entity number requirement. If so, a new target group queue is created, the next entity of the target entity is determined as the target entity and marked in the target group queue, and the step of determining the next entity of the target entity from the target first entity group is continued until there is no next entity of the target entity; if not, the step of determining the next entity of the target entity from the target first entity group is continued until there is no next entity of the target entity.

[0078] As some examples, the predetermined overlapping position difference requirement can be understood as being less than a preset overlapping position difference threshold, and the second position difference between the two entities can be determined to be in an overlapping state in the second direction if it is less than the preset overlapping position difference threshold. The predetermined overlapping entity quantity requirement can be understood as being less than a preset overlapping entity threshold (which can be set according to actual needs, and is set to 2 as an example below).

[0079] As some examples, Figure 7B As shown, Figure 7B FIG. 1 is a top view schematic diagram of shelf overlap in a shelf blocking scenario according to some embodiments of the present disclosure. Figure 7B Taking entity 710-2 as an example, entity 710-2 has overlapping entities in the longitudinal direction (entity 710-3, entity 710-4, entity 710-5, entity 710-6, entity 710-7), and the longitudinal position differences between entity 710-4, entity 710-5, entity 710-6, entity 710-7 and entity 710-2 are all greater than the lane width, that is, it is considered that the second position difference between the multiple overlapping entities of entity 710-2 and entity 710-2 in the second direction does not meet the predetermined overlapping position difference requirement, and therefore it can be determined that there is no lane at the position of entity 710-2.

[0080] As some examples, in Fig. 7A In the figure, entity 710-1 has 0 overlapping entities in the vertical direction, which is less than 2. That is, it can be considered that in the case of vertical grouping, there is an aisle at the position of entity 710-1. Therefore, the entity to the right of entity 710-1 is marked in the newly created target grouping queue to divide entity 710-1 and the entity to the right of entity 710-1 into different second entity groups.

[0081] like Figure 7C As shown, Figure 7C A schematic top view of the shelf separation result in a shelf blocking scenario according to some embodiments of the present disclosure is shown. Fig. 7A The shelf blocking word of entity 710-1 can be Figure 7C As shown, entity 710-1 is marked at the head of the target group queue, so that entity 710-8 can be determined as the target entity, and the step of determining the next entity of the target entity (ie, entity 710-9) from the target first entity group is continued until there is no next entity of the target entity.

[0082] Back to Figure 2 At box 240, the electronic device 110 creates three-dimensional models corresponding to each of the multiple entities based on the multiple second entity groups, the entity attribute information, and the label position information corresponding to each entity in the multiple second entity groups.

[0083] In some embodiments, based on label position information corresponding to each entity in a plurality of second entity groups, the grouping category corresponding to each of the plurality of entity groups is determined; based on the grouping category corresponding to each of the plurality of entity groups and the label position information corresponding to each of the plurality of second entity groups, the entity posture information corresponding to each of the plurality of entity groups is determined; and based on the entity attribute information, the label position information corresponding to each of the plurality of second entity groups, and the entity posture information corresponding to each of the plurality of entity groups, a three-dimensional model corresponding to each of the plurality of entities is created.

[0084] As some examples, the grouping categories include back-to-back grouping, single-row grouping, etc. Back-to-back grouping is, for example, Figure 3A As shown in box 310 in FIG. 1 , a single row grouping is, for example, Figure 3A As shown in box 330 in . In each second entity group, based on the label position information of the multiple entities contained therein, it can be determined whether the entities contained therein are in a single row or back to back, and the grouping category of each second entity group is determined based on this.

[0085] In some embodiments, when it is determined that the grouping category of the target second entity grouping is a back-to-back entity grouping, based on the label position information corresponding to each entity in the target second entity grouping, the entity posture information corresponding to each entity in the target second entity grouping is determined; or when it is determined that the grouping category of the target second entity grouping is a one-sided entity grouping, based on the label position information corresponding to each entity in the target second entity grouping, the adjacent second entity grouping of the target second entity grouping is determined, and based on the relative position relationship between the target second entity grouping and the adjacent second entity grouping, the entity posture information corresponding to each entity in the target second entity grouping is determined.

[0086] As some examples, Figure 3AAs shown, for the back-to-back grouping (as shown in box 310), it can be determined that the two sides of the back-to-back grouping are the front of the shelf according to the arrangement direction (that is, the top and bottom are the front), and for the single-row grouping (as shown in box 330), it can be determined based on the relative position relationship between its adjacent second entity grouping (that is, the entity grouping shown in box 320) and the single-row grouping, as shown in FIG. Figure 3A As shown, the physical grouping of the single-row grouping shown in box 330 is located above the back-to-back grouping shown in box 320, that is, the lower side of the single-row grouping shown in box 330 faces the back-to-back grouping shown in box 320. It can be determined that the lower side of the single-row grouping shown in box 330 is the front of the shelf.

[0087] Based on this, the entity pose information including the front and back sides of the entity can be determined. Based on the entity attribute information, the label position information corresponding to each entity in the multiple second entity groups, and the entity pose information corresponding to each entity in the multiple entity groups, the shape, size, position and other information of the three-dimensional models of the multiple entities can be determined, thereby creating three-dimensional models corresponding to the multiple entities.

[0088] The following describes the beneficial effects that the three-dimensional modeling method of the present invention can bring compared with the traditional modeling method.

[0089] On the one hand, the three-dimensional modeling method disclosed in the present invention does not need to use acquisition equipment to collect information, saving equipment resources. In addition, there is no need to store, process and process the information collected by the acquisition equipment, saving the computing resources and physical resources of the electronic equipment and improving the modeling efficiency of three-dimensional modeling.

[0090] On the other hand, the three-dimensional modeling method disclosed in the present invention can automatically determine the pose information of an entity without the need for manual annotation, thus saving human resources and avoiding time-consuming labor, and further improving the processing efficiency of creating accurate three-dimensional models.

[0091] In summary, the 3D modeling method disclosed in the present invention can improve the modeling efficiency of creating 3D models of multiple entities and reduce the computing resource consumption of 3D modeling while ensuring the effects of the 3D models of multiple entities.

[0092] The embodiments of the present disclosure also provide corresponding devices for implementing the above methods or processes. Figure 8 A schematic structural block diagram of an apparatus 800 for acoustic processing according to some embodiments of the present disclosure is shown. The apparatus 800 may be implemented as or included in the electronic device 110. Each module / component in the apparatus 800 may be implemented by hardware, software, firmware or any combination thereof.

[0093] like Figure 8As shown, the device 800 includes an information determination module 810, which is configured to determine entity attribute information of multiple entities and label position information corresponding to labels respectively attached to the multiple entities, the label position information includes first label position information and second label position information, the first label position information and the second label position information represent the position information of the corresponding entity in different directions; a first grouping module 820, which is configured to group the multiple entities based on the first label position information to obtain multiple first entity groups, each first entity group includes at least one entity among the multiple entities; a second group determination module 830, which is configured to group the entities in each first entity group based on the second label position information of the entities in each first entity group to obtain multiple second entity groups, each second entity group includes at least one entity in the first entity group; and a modeling module 840, which is configured to create three-dimensional models corresponding to each of the multiple entities based on the multiple second entity groups, the entity attribute information, and the label position information corresponding to each entity in the multiple second entity groups.

[0094] In some embodiments, the first grouping module 820 is further configured to: determine first position difference information between multiple entities in the first direction based on position information of corresponding entities indicated by first tag position information of multiple entities; and group multiple entities based on the first position difference information to obtain multiple first entity groups, and the first position difference information between any two entities in any entity group meets a predetermined first position difference requirement.

[0095] In some embodiments, the second grouping determination module 830 is further configured to: determine each first entity group as a target first entity group in turn; group the entities in the target first entity group based on the second label position information of the entities in the target first entity group to obtain multiple sub-entity groups corresponding to the target first entity group; and obtain multiple second entity groups based on the multiple sub-entity groups corresponding to the target first entity group.

[0096] In some embodiments, the second grouping determination module 830 is further configured to: sort each entity in the target first entity group based on the position information of the corresponding entity in the second direction indicated by the second label position information of the entity in the target first entity group, and obtain the entity sorting result corresponding to the target first entity group; and group the entities in the target first entity group based on the entity sorting result and the position information of the corresponding entity in the second direction indicated by the second label position information of the entity in the target first entity group, so as to obtain multiple sub-entity groups corresponding to the target first entity group.

[0097] In some embodiments, the second group determination module 830 is further configured to: determine the first entity from the target first entity group as the target entity based on the entity sorting result; determine the target group queue and mark the target entity to the target group queue; determine the next entity of the target entity from the target first entity group based on the entity sorting result, and determine the second position difference information between the target entity and the next entity in the second direction based on the second label information of the target entity and the second label information of the next entity; determine whether the second information difference information meets the preset second position difference requirement, if so, mark the next entity to the group queue, and determine the next entity as the target entity, and continue to perform the step of determining the next entity of the target entity from the target first entity group until the next entity of the target entity does not exist, if not, create a new target group queue, determine the next entity as the target entity, and continue to perform the step of determining the next entity of the target entity from the target first entity group until the next entity of the target entity does not exist; and group the entities in the target first entity group based on the entities marked in each target group queue.

[0098] In some embodiments, the second group determination module 830 is further configured to: mark the next entity into the group queue, and determine the next entity as the target entity; based on the second tag position information of the target entity, determine multiple overlapping entities corresponding to the target entity from multiple entities, and the second position difference between the multiple overlapping entities and the target entity in the second direction meets the predetermined overlapping position difference requirement; and determine whether the number of multiple overlapping entities meets the predetermined overlapping entity number requirement, if so, create a new target group queue, determine the next entity of the target entity as the target entity and mark it in the target group queue, and continue to execute the step of determining the next entity of the target entity from the target first entity group until there is no next entity of the target entity; if not, continue to execute the step of determining the next entity of the target entity from the target first entity group until there is no next entity of the target entity.

[0099] In some embodiments, the device 800 also includes an entity determination module, which is configured to determine multiple initial entities and initial label position information corresponding to labels respectively affixed to the multiple initial entities; determine an arrangement direction of the multiple initial entities based on the initial label position information corresponding to labels respectively affixed to the multiple initial entities; and determine multiple entities from the multiple initial entities based on the arrangement direction of the multiple initial entities and a predetermined arrangement direction requirement.

[0100] In some embodiments, the modeling module 840 is further configured to determine the grouping category corresponding to each of the multiple entity groupings based on the label position information corresponding to each entity in the multiple second entity groupings; determine the entity posture information corresponding to each entity in the multiple entity groupings based on the grouping category corresponding to each of the multiple entity groupings and the label position information corresponding to each entity in the multiple second entity groupings; and create a three-dimensional model corresponding to each of the multiple entities based on the entity attribute information, the label position information corresponding to each entity in the multiple second entity groupings, and the entity posture information corresponding to each entity in the multiple entity groupings.

[0101] In some embodiments, the modeling module 840 is further configured to determine the entity posture information corresponding to each entity in the target second entity grouping based on the label position information corresponding to each entity in the target second entity grouping when the grouping category of the target second entity grouping is determined to be a back-to-back entity grouping; or to determine the adjacent second entity grouping of the target second entity grouping based on the label position information corresponding to each entity in the target second entity grouping when the grouping category of the target second entity grouping is determined to be a one-sided entity grouping, and determine the entity posture information corresponding to each entity in the target second entity grouping based on the relative position relationship between the target second entity grouping and the adjacent second entity grouping.

[0102] In some embodiments, the plurality of entities are a plurality of shelves, and the labels are shelf labels.

[0103] The units and / or modules included in the device 800 can be implemented in various ways, including software, hardware, firmware or any combination thereof. In some embodiments, one or more units and / or modules can be implemented using software and / or firmware, such as machine executable instructions stored on a storage medium. In addition to or as an alternative to machine executable instructions, some or all of the units and / or modules in the device 800 can be implemented at least in part by one or more hardware logic components. As an example and not limitation, exemplary types of hardware logic components that can be used include field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0104] It should be understood that one or more steps in the above method can be performed by a suitable electronic device or a combination of electronic devices. Such an electronic device or a combination of electronic devices may include, for example, Figure 1 The electronic device 110 in.

[0105] Fig. 9 900 is a block diagram of an electronic device in which one or more embodiments of the present disclosure may be implemented. It should be understood that Fig. 9The electronic device 900 shown is merely exemplary and should not constitute any limitation on the functionality and scope of the embodiments described herein. Fig. 9 The electronic device 900 shown can be used to implement Figure 1 Electronic device 110 or Figure 8 Device 800.

[0106] like Fig. 9 As shown, the electronic device 900 is in the form of a general electronic device. The components of the electronic device 900 may include, but are not limited to, one or more processors or processing units 910, a memory 920, a storage device 930, one or more communication units 940, one or more input devices 950, and one or more output devices 960. The processing unit 910 may be an actual or virtual processor and is capable of performing various processes according to a program stored in the memory 920. In a multi-processor system, multiple processing units execute computer executable instructions in parallel to improve the parallel processing capability of the electronic device 900.

[0107] The electronic device 900 typically includes a plurality of computer storage media. Such media can be any available media accessible to the electronic device 900, including but not limited to volatile and non-volatile media, removable and non-removable media. The memory 920 can be a volatile memory (e.g., register, cache, random access memory (RAM)), a non-volatile memory (e.g., a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), flash memory) or some combination thereof. The storage device 930 can be a removable or non-removable medium, and can include a machine-readable medium, such as a flash drive, a disk, or any other medium, which can be used to store information and / or data and can be accessed within the electronic device 900.

[0108] The electronic device 900 may further include additional removable / non-removable, volatile / non-volatile storage media. Fig. 9 As shown in , a disk drive for reading or writing from a removable, non-volatile disk (e.g., a "floppy disk") and an optical drive for reading or writing from a removable, non-volatile optical disk may be provided. In these cases, each drive may be connected to the bus (not shown) by one or more data media interfaces. Memory 920 may include a computer program product 925 having one or more program modules that are configured to perform various methods or actions of various embodiments of the present disclosure.

[0109] The communication unit 940 implements communication with other electronic devices through a communication medium. Additionally, the functions of the components of the electronic device 900 can be implemented with a single computing cluster or multiple computing machines that can communicate through a communication connection. Therefore, the electronic device 900 can operate in a networked environment using a logical connection with one or more other servers, a network personal computer (PC), or another network node.

[0110] The input device 950 may be one or more input devices, such as a mouse, a keyboard, a tracking ball, etc. The output device 960 may be one or more output devices, such as a display, a speaker, a printer, etc. The electronic device 900 may also communicate with one or more external devices (not shown) through the communication unit 940 as needed, such as a storage device, a display device, etc., communicate with one or more devices that allow a user to interact with the electronic device 900, or communicate with any device that allows the electronic device 900 to communicate with one or more other electronic devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface (not shown).

[0111] According to an exemplary implementation of the present disclosure, a computer-readable storage medium is provided, on which computer-executable instructions are stored, wherein the computer-executable instructions are executed by a processor to implement the method described above. According to an exemplary implementation of the present disclosure, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, and the computer-executable instructions are executed by a processor to implement the method described above.

[0112] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices, equipment, and computer program products implemented according to the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0113] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0114] Computer-readable program instructions can be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, so that the instructions executed on the computer, other programmable data processing apparatus, or other device implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0115] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple implementations of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of a module, program segment or instruction includes one or more executable instructions for realizing the logical function of the specification. In some implementations as replacements, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be realized by a special hardware-based system that performs the function or action of the specification, or can be realized by a combination of special hardware and computer instructions.

[0116] The above descriptions of various implementations of the present disclosure are exemplary, non-exhaustive, and not limited to the disclosed implementations. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described implementations. The selection of terms used herein is intended to best explain the principles of the implementations, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the various implementations disclosed herein.

Claims

1. A three-dimensional modeling method, comprising: Determine entity attribute information of a plurality of entities and label position information corresponding to labels respectively attached to the plurality of entities, wherein the label position information includes first label position information and second label position information, wherein the first label position information and the second label position information indicate position information of the corresponding entity in different directions; Based on the first tag location information, the multiple entities are grouped to obtain multiple first entity groups, each of which includes at least one entity among the multiple entities; In each first entity group, based on the second label position information of the entity in each first entity group, the entities in each first entity group are grouped to obtain a plurality of second entity groups, each second entity group including at least one entity in the first entity group; as well as Based on the plurality of second entity groups, the entity attribute information, and label position information corresponding to each entity in the plurality of second entity groups, a three-dimensional model corresponding to each of the plurality of entities is created.

2. The method according to claim 1, wherein grouping the plurality of entities based on the first tag location information to obtain the plurality of first entity groups comprises: Determine first position difference information between the multiple entities in the first direction based on position information of corresponding entities indicated by the first tag position information of the multiple entities; as well as The multiple entities are grouped based on the first position difference information to obtain the multiple first entity groups, and the first position difference information between any two entities in any entity group meets a predetermined first position difference requirement.

3. The method according to claim 1 or 2, wherein grouping the entities in each first entity group based on the second tag position information of the entities in each first entity group to obtain the plurality of second entity groups comprises: sequentially determining each of the first entity groups as a target first entity group; Based on the second label position information of the entity in the target first entity group, grouping the entities in the target first entity group to obtain a plurality of sub-entity groups corresponding to the target first entity group; as well as The plurality of second entity groups are obtained based on the plurality of sub-entity groups corresponding to the target first entity group.

4. The method according to claim 3, wherein grouping the entities in the target first entity group based on the second tag position information of the entities in the target first entity group to obtain a plurality of sub-entity groups corresponding to the target first entity group comprises: Based on the position information of the corresponding entity in the second direction indicated by the second label position information of the entity in the target first entity group, sorting each entity in the target first entity group to obtain an entity sorting result corresponding to the target first entity group; as well as Based on the entity sorting result and the position information of the corresponding entity in the second direction indicated by the second label position information of the entity in the target first entity group, the entities in the target first entity group are grouped to obtain multiple sub-entity groups corresponding to the target first entity group.

5. The method according to claim 4, wherein grouping the entities in the target first entity group based on the entity ranking result and the second label position information of the entities in the target first entity group comprises: Based on the entity ranking result, determining the first entity from the target first entity group as the target entity; Determine a target group queue, and mark the target entity into the target group queue; Based on the entity sorting result, determine the next entity of the target entity from the target first entity group, and based on the second label information of the target entity and the second label information of the next entity, determine the second position difference information between the target entity and the next entity in the second direction; Determine whether the second information difference information meets the preset second position difference requirement, If yes, the next entity is marked in the group queue, and the next entity is determined as the target entity, and the step of determining the next entity of the target entity from the target first entity group is continued until there is no next entity of the target entity. If not, a new target group queue is created, the next entity is determined as the target entity, and the step of determining the next entity of the target entity from the target first entity group is continued until there is no next entity of the target entity; and The entities in the target first entity group are grouped based on the entities marked by each target group queue.

6. The method according to claim 5, wherein marking the next entity into the grouping queue, determining the next entity as a target entity, and continuing to perform the step of determining the next entity of the target entity from the target first entity group until the target entity does not have a next entity comprises: marking the next entity into the grouping queue, and determining the next entity as a target entity; Based on the second label position information of the target entity, determining a plurality of overlapping entities corresponding to the target entity from the plurality of entities, wherein a second position difference between the plurality of overlapping entities and the target entity in the second direction meets a predetermined overlapping position difference requirement; as well as determining whether the number of the plurality of overlapping entities meets a predetermined overlapping entity number requirement, If yes, a new target group queue is created, the next entity of the target entity is determined as the target entity and marked in the target group queue, and the step of determining the next entity of the target entity from the target first entity group is continued until there is no next entity of the target entity; If not, continue to execute the step of determining the next entity of the target entity from the target first entity group until there is no next entity of the target entity.

7. The method according to claim 1, further comprising: Determine a plurality of initial entities and initial label position information corresponding to labels respectively attached to the plurality of initial entities; Determining arrangement directions of the multiple initial entities based on initial label position information corresponding to labels attached to the multiple initial entities; as well as The multiple entities are determined from the multiple initial entities based on the arrangement directions of the multiple initial entities and a predetermined arrangement direction requirement.

8. The method according to claim 1, wherein based on the plurality of second entity groups, the entity attribute information, and label position information corresponding to each entity in the plurality of second entity groups, creating a three-dimensional model corresponding to each of the plurality of entities comprises: Determining the grouping categories corresponding to each of the plurality of entity groups based on the label position information corresponding to each entity in the plurality of second entity groups; Determine entity pose information corresponding to each entity in the plurality of entity groups based on the group categories corresponding to each of the plurality of entity groups and the label position information corresponding to each entity in the plurality of second entity groups; as well as Based on the entity attribute information, label position information corresponding to each entity in the plurality of second entity groups, and entity posture information corresponding to each entity in the plurality of entity groups, a three-dimensional model corresponding to each of the plurality of entities is created.

9. The method according to claim 8, wherein determining entity pose information corresponding to each entity in the plurality of entity groups comprises: In a case where it is determined that the grouping category of the target second entity group is a back-to-back entity group, determining entity pose information corresponding to each entity in the target second entity group based on label position information corresponding to each entity in the target second entity group; or When it is determined that the grouping category of the target second entity grouping is a one-sided entity grouping, the adjacent second entity grouping of the target second entity grouping is determined based on the label position information corresponding to each entity in the target second entity grouping, and the entity posture information corresponding to each entity in the target second entity grouping is determined based on the relative position relationship between the target second entity grouping and the adjacent second entity grouping.

10. The method according to claim 1, wherein the plurality of entities are a plurality of shelves, and the labels are shelf labels.

11. A device for three-dimensional modeling, comprising: an information determination module, configured to determine entity attribute information of a plurality of entities and label position information corresponding to labels respectively attached to the plurality of entities, the label position information comprising first label position information and second label position information, the first label position information and the second label position information representing position information of the corresponding entity in different directions; A first grouping module is configured to group the multiple entities based on the first tag location information to obtain multiple first entity groups, each of which includes at least one entity among the multiple entities; A second group determination module is configured to group the entities in each first entity group based on the second label position information of the entities in each first entity group to obtain a plurality of second entity groups, each second entity group including at least one entity in the first entity group; as well as The modeling module is configured to create three-dimensional models corresponding to each of the plurality of entities based on the plurality of second entity groups, the entity attribute information, and label position information corresponding to each entity in the plurality of second entity groups.

12. An electronic device comprising: at least one processing unit; as well as At least one memory, the at least one memory being coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions causing the electronic device to perform the method according to any one of claims 1 to 10 when executed by the at least one processing unit.

13. A computer-readable storage medium having a computer program stored thereon, wherein the computer program can be executed by a processor to implement the method according to any one of claims 1 to 10.

14. A computer program product tangibly stored in a computer storage medium and comprising computer executable instructions which, when executed by a device, cause the device to perform the method according to any one of claims 1 to 10.

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