Alignment processing method and apparatus for three-dimensional face model, device, and medium

Abstract

Embodiments of the present disclosure relate to an alignment processing method and apparatus for a three-dimensional face model, a device, and a medium. The method comprises: in response to acquiring an alignment request for a three-dimensional face model, recognizing a plurality of face key points on the three-dimensional face model on the basis of a preset recognition algorithm; displaying the plurality of face key points on the three-dimensional face model; in response to acquiring a modification operation of a user on at least one face key point among the plurality of face key points, determining a plurality of modified face key points; and aligning the three-dimensional face model on the basis of the plurality of modified face key points. In the present technical solution, target key points in the three-dimensional face model are determined by combining a preset algorithm and a modification operation of a user, and alignment of the three-dimensional face model is implemented on the basis of the target key points, thereby not only improving the alignment efficiency but also ensuring the alignment effect.

Description

Alignment processing method, device and equipment of three-dimensional face model and medium

[0001] The present application claims priority to the Chinese patent application No. 202410697746.6, filed on May 31, 2024, and entitled "Alignment processing method, device and equipment of three-dimensional face model and medium", the whole content of which is incorporated herein by reference. TECHNICAL FIELD

[0002] The present disclosure relates to the technical field of three-dimensional model, and particularly relates to an alignment processing method, device and equipment of three-dimensional face model and medium. BACKGROUND

[0003] With the development of three-dimensional scanning technology, it is common to meet some scene requirements based on a three-dimensional face model, such as designing teeth and designing smiles based on a three-dimensional face model. In order to ensure the meeting effect of related requirements, it is common to align the three-dimensional face model. For example, aligning the head position as a premise can make the observation angle of the teeth more standard.

[0004] In the related art, the user is prompted in advance to control the head angle according to the alignment position, and then a plurality of two-dimensional images of the user's head are captured. After obtaining the three-dimensional face model, the three-dimensional face model is moved to a plurality of reference positions, and a plurality of reference images under the plurality of reference positions are captured. The plurality of reference images and the plurality of two-dimensional images are matched, the reference position with a matching success is determined as the position of the aligned head position, and then the three-dimensional face model is aligned to the corresponding reference position.

[0005] However, in the above-mentioned alignment method of the three-dimensional face model, a plurality of data needs to be obtained, including a plurality of two-dimensional images and a plurality of reference images under a plurality of reference positions. The acquisition efficiency of each kind of data is low, which leads to a low alignment efficiency of the three-dimensional face model. SUMMARY

[0006] In order to solve the above technical problems or at least partially solve the above technical problems, the present disclosure provides an alignment processing method, device and equipment of three-dimensional face model and medium to solve the technical problem of low alignment efficiency of the three-dimensional face model in the prior art.

[0007] The embodiment of the present disclosure provides a three-dimensional face model alignment processing method, which comprises the following steps: in response to obtaining an alignment request of a three-dimensional face model, identifying a plurality of face key points on the three-dimensional face model according to a preset identification algorithm; displaying the plurality of face key points on the three-dimensional face model; in response to obtaining a modification operation of a user on at least one face key point in the plurality of face key points, determining a plurality of modified face key points; and aligning the three-dimensional face model according to the plurality of modified face key points.

[0008] The embodiment of the present disclosure also provides a three-dimensional face model alignment processing device, which comprises the following modules: an identification module configured to, in response to obtaining an alignment request of a three-dimensional face model, identify a plurality of face key points on the three-dimensional face model according to a preset identification algorithm; a display module configured to display the plurality of face key points on the three-dimensional face model; a determination module configured to, in response to obtaining a modification operation of a user on at least one face key point in the plurality of face key points, determine a plurality of modified face key points; and an alignment module configured to align the three-dimensional face model according to the plurality of modified face key points.

[0009] The embodiment of the present disclosure also provides an electronic device, which comprises a processor, a memory configured to store processor-executable instructions, and the processor configured to read the executable instructions from the memory and execute the instructions to implement the three-dimensional face model alignment processing method provided by the embodiment of the present disclosure.

[0010] The embodiment of the present disclosure also provides a computer-readable storage medium, which stores a computer program configured to execute the three-dimensional face model alignment processing method provided by the embodiment of the present disclosure.

[0011] Compared with the prior art, the technical scheme provided by the embodiment of the present disclosure has the following advantages:

[0012] The three-dimensional face model alignment processing scheme provided by the embodiment of the present disclosure comprises the following steps: in response to obtaining an alignment request of a three-dimensional face model, identifying a plurality of face key points on the three-dimensional face model according to a preset identification algorithm; displaying the plurality of face key points on the three-dimensional face model; in response to obtaining a modification operation of a user on at least one face key point in the plurality of face key points, determining a plurality of modified face key points; and aligning the three-dimensional face model according to the plurality of modified face key points. In the technical scheme, the target key point in the three-dimensional face model is determined by combining the preset algorithm and the modification operation of the user, and the three-dimensional face model is aligned according to the target key point, which not only improves the alignment efficiency, but also guarantees the alignment effect. BRIEF DESCRIPTION OF DRAWINGS

[0013] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0014] Figure 1 is a flowchart illustrating a method for correcting a three-dimensional face model according to an embodiment of this disclosure.

[0015] Figure 2 is a schematic diagram of target key points of a three-dimensional face model provided in an embodiment of this disclosure.

[0016] Figure 3 is a flowchart illustrating another method for correcting a three-dimensional face model provided in an embodiment of this disclosure.

[0017] Figure 4A is a schematic diagram of a mouth image provided in an embodiment of this disclosure.

[0018] Figure 4B is a schematic diagram of another mouth image provided in an embodiment of this disclosure.

[0019] Figure 5 is a flowchart illustrating another method for correcting a three-dimensional face model provided in an embodiment of this disclosure.

[0020] Figure 6 is a schematic diagram of an application scenario of a straightened three-dimensional face model provided according to an embodiment of the present disclosure.

[0021] Figure 7 is a schematic diagram of the structure of a three-dimensional face model straightening processing device provided in an embodiment of this disclosure.

[0022] Figure 8 is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0023] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0024] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0025] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0026] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0027] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0028] To address the aforementioned issues, this disclosure provides a method for correcting a three-dimensional face model. The method will be described below with reference to specific embodiments.

[0029] Figure 1 is a flowchart illustrating a method for correcting a 3D face model according to an embodiment of this disclosure. This method can be executed by a 3D face model correcting device, which can be implemented using software and / or hardware and is generally integrated into an electronic device. As shown in Figure 1, the method includes:

[0030] Step 101: In response to receiving a request to align the 3D face model, identify multiple facial key points on the 3D face model according to a preset recognition algorithm.

[0031] The execution method of the alignment request for the 3D face model varies in different application scenarios. In some possible embodiments, an alignment control can be set in advance in the processing platform of the application scenario. After the 3D face model is obtained, if the alignment control is detected to be triggered, an alignment request for the 3D face model is obtained.

[0032] In one embodiment of this disclosure, in response to a request to align a 3D face model, multiple facial key points on the 3D face model are identified according to a preset recognition algorithm. The preset recognition algorithm includes, but is not limited to, artificial intelligence machine learning algorithms and deep learning algorithms. The multiple facial key points on the 3D face model can be key points corresponding to the alignment position. For example, when the alignment position is a natural head position, the corresponding facial key points include key points defining the orbitoauricular plane (e.g., the left and right infraorbital margins and the right superior margin of the external auditory canal), and key points defining the midsagittal plane (e.g., the premental point, the tip of the nose, and the forehead point).

[0033] Step 102: Display multiple facial key points on the 3D face model.

[0034] In one embodiment of this disclosure, a three-dimensional face model can be displayed on a processing platform for a relevant application scenario, and multiple facial key points can be displayed on the three-dimensional face model, that is, multiple facial key points can be displayed intuitively, so that users can make subsequent modifications to the facial key points.

[0035] In one embodiment of this disclosure, multiple views of a three-dimensional face model can also be determined, displaying multiple facial key points in a two-dimensional form.

[0036] Step 103: In response to receiving a user's modification operation on at least one of the multiple facial key points, determine the modified multiple facial key points.

[0037] It should be understood that, in order to further ensure the reliability of facial key points, in one embodiment of this disclosure, user modification operations on facial key points are also obtained, so that users can manually modify facial key points.

[0038] In some possible embodiments, in response to a user's selection of at least one facial key point, a movement operation on the at least one facial key point corresponding to the selection operation is obtained. For example, after a user selects facial key point P1, if a movement operation of dragging P1 is detected, it is determined that the movement operation is a modification operation on P1. The specific operation methods of the selection and movement operations can be defined according to the needs of the scenario and are not limited here. For example, the selection operation can be a trigger operation with a trigger time greater than a preset time threshold, and the movement operation can be a gesture trajectory operation of pressing and holding the selected facial key point. In this embodiment, the user can modify the facial key points through simple modification operations, which is highly operable and flexible.

[0039] In this embodiment, in response to the user's modification operation on facial key points, multiple modified facial key points are determined, that is, at least one facial key point has been modified by the user.

[0040] In some possible implementations, if no user modification is detected, the 3D face model is directly aligned based on multiple facial key points.

[0041] Step 104: Align the 3D face model based on the modified multiple facial key points.

[0042] After determining the modified facial key points, the 3D face model is aligned based on these key points. Therefore, 3D face model alignment can be achieved solely based on facial key points, eliminating the need for acquiring multiple types of data and significantly improving the efficiency of 3D face model alignment.

[0043] In some possible embodiments, the alignment position corresponding to the alignment request can be determined, at least one reference direction corresponding to the alignment position can be determined, the facial key points associated with each reference direction can be determined among the modified multiple facial key points, and the display surface of the 3D face model can be adjusted according to each reference direction and the associated facial key points, thereby achieving the alignment of the 3D face model.

[0044] In this example, when the head is positioned in a natural head position, the modified facial key points are divided into a first key point set and a second key point set. The first key point set is associated with the orbitoauricular plane. For example, referring to Figure 2, the target key points included in the first key point set (the solid black dots in the figure) include at least the left and right inferior orbital margins and the right superior margin of the external auditory canal. The second key point set is associated with the midsagittal plane. For example, continuing to refer to Figure 2, the target key points included in the second key point set (the hollow gray dots in the figure) include at least the premental point, the tip of the nose, and the forehead point. Referring to Figure 2, in this example, the orbitoauricular plane of the 3D face model is determined based on the first key point set, and the midsagittal plane of the 3D face model is determined based on the second key point set. Then, the 3D face model is aligned based on the orbitoauricular plane and the midsagittal plane.

[0045] For example, the horizontal and vertical display planes of the preset display screen on the processing platform corresponding to the application scenario are determined. The 3D face model is then aligned according to these planes. The orbital-auricular plane and the midsagittal plane of the aligned 3D face model are parallel to the horizontal and vertical display planes, respectively. For instance, the generated orbital-auricular plane can be aligned parallel to the horizontal display plane, and then the midsagittal plane can be aligned parallel to the vertical display plane. Referring to Figure 2, the aligned 3D face model visually displays a frontal view of the face.

[0046] In summary, the three-dimensional face model alignment method of this disclosure, in response to receiving an alignment request for the three-dimensional face model, identifies multiple facial key points on the three-dimensional face model according to a preset recognition algorithm, displays the multiple facial key points on the three-dimensional face model, and then, in response to receiving a user's modification operation on the facial key points, determines the modified multiple facial key points, and aligns the three-dimensional face model according to the modified multiple facial key points. In this technical solution, by combining the preset algorithm and the user's modification operation to determine the target key points in the three-dimensional face model, and aligning the three-dimensional face model according to the target key points, not only is the alignment efficiency improved, but the alignment effect is also guaranteed.

[0047] Based on the above embodiments, after the 3D face model is aligned, the aligned 3D face model can better meet the needs of users in relevant application scenarios. The following is an example illustration with specific embodiments.

[0048] In one example of this disclosure, as shown in Figure 3, after the 3D face model is aligned according to the modified facial key points, the following steps S301 to S303 are also included.

[0049] Step 301: Determine the front view of the face of the 3D face model after it has been aligned.

[0050] In this embodiment, the front view of the 3D face model after it has been aligned can be directly photographed to obtain the corresponding front view of the face.

[0051] Step 302: In response to the request to obtain smile information, determine the mouth image region in the front view of the face.

[0052] In this embodiment, in response to a request to obtain smile information, the mouth image region in the front view of the face is determined. For example, the front view of the face can be input into a pre-trained segmentation model to determine the mouth image region in the front view of the face.

[0053] Step 303: Obtain the smile information corresponding to the request based on the mouth image region recognition.

[0054] In this embodiment, smile information corresponding to the request is obtained based on the mouth image region recognition. The smile information is obtained from a frontal view of the face of a properly aligned 3D face model, ensuring the reliability of the observation angle and avoiding errors in the obtained smile information due to deviations in the observation angle.

[0055] In different application scenarios, the smile information is different. For example, in one embodiment, when the smile information includes the standardity of the smile line, the smile information corresponding to the request is obtained based on the mouth image region recognition, including: recognizing the smile curve, the upper edge curve of the lower lip and the smile cheek corridor based on the mouth image region. Referring to Figure 4B, for a standard smile, the curve matching degree between the smile curve and the upper edge curve of the lower lip should be high. The curve matching degree mainly refers to the parallelism of the two arcs, and can also refer to parameters such as the curvature and distance of the two arcs.

[0056] Parallel curves refer to two curves that point in the same direction on a plane and whose distance remains constant; that is, the shortest distance from any point on one curve to the other is equal. Referring to Figure 4A, the cheek area of ​​a standard smile is also relatively appropriate. Therefore, in this example, the curve matching degree between the smile curve and the upper edge of the lower lip is determined, and the cheek area of ​​the smile is determined. Based on the curve matching degree and the cheek area, the standard degree of the smile line is determined.

[0057] The method of determining the standard of the smile line based on the curve matching degree and the cheek area varies in different application scenarios.

[0058] In some possible examples, a first weight corresponding to the curve matching degree is determined, and a second weight for the cheek area is determined. A first difference between the curve matching degree and the preset standard curve matching degree is calculated. A first ratio of the first difference to the preset standard curve is calculated, a second ratio of the cheek area to the entire mouth area is calculated, and a second difference between the second ratio and the preset standard area ratio is calculated. A first product of the first ratio and the preset first standard score is calculated, and a second product of the second ratio and the preset second standard score is calculated. A first summation of the first standard score and the first product is calculated, a second summation of the second standard score and the second standard score is calculated, and a third product of the first summation and the first weight is calculated. A fourth product of the second summation and the second weight is calculated, and the sum of the third and fourth products is calculated. The sum of the third and fourth products is used as the smile line standard.

[0059] In some possible examples, the curve difference between the curve matching degree and the preset standard curve matching degree can be calculated, and a first preset relationship can be consulted to determine the first reference standard degree corresponding to the curve difference. The area difference between the cheek area and the preset standard cheek area can be calculated, and a second preset relationship can be consulted to determine the second reference standard degree corresponding to the area difference. The average of the first reference standard degree and the second reference standard degree can be calculated, and this average value can be used as the smile line standard degree.

[0060] In some possible examples, the curve matching degree and the cheek area of ​​the smile cheek can be input into a pre-built convolutional neural network model to obtain the smile line standard degree output by the convolutional neural network model.

[0061] In one example of this disclosure, as shown in Figure 5, after the 3D face model is aligned according to the modified facial key points, the following steps S501 to S503 are also included.

[0062] Step 501: In response to the request to obtain facial three-part information, identify multiple sets of three-part feature points in the corrected 3D face model, wherein each set of three-part feature points is located on the same plane perpendicular to the orbital-auricular plane of the 3D face model.

[0063] Each group of three facial feature points includes the hairline point (Tr), the glabella point (G), the subnasal point (Sn), and the subchinal point (Me). Each feature point group contains at least one feature point. If a feature point group contains multiple feature points, then all feature points in that group are located on the same horizontal plane.

[0064] Step 502: Generate a reference plane parallel to the horizontal plane based on each of the three court feature points to obtain multiple reference planes.

[0065] Step 503: Obtain the length and proportion of the three courts based on the planar distance between multiple reference planes.

[0066] In the embodiments of this disclosure, a reference plane parallel to the horizontal plane is generated based on each feature point of the three courts to obtain multiple reference planes. Then, the length and proportion of the three courts are obtained based on the planar distance between the multiple reference planes.

[0067] For example, in an embodiment of this disclosure, as shown in Figure 6, a corresponding reference plane A can be generated based on the Tr feature point group, a reference plane B can be generated based on the glabella G feature point group, a corresponding reference plane C can be generated based on the subnasal point Sn feature point group, and a corresponding reference plane D can be generated based on the subchinal point Me feature point group. The planar distance L1 between reference plane A and reference plane B is calculated as the upper court length, the planar distance L2 between reference plane B and reference plane C is calculated as the middle court length, and the planar distance L3 between reference plane C and reference plane D is calculated as the lower court length. The proportion of the three courts can be determined based on the length ratios between the three courts. Specifically, the three courts include the upper court, the middle court, and the lower court. The length ratios are calculated based on the upper court length, the middle court length, and the lower court length. The proportion of the three courts is determined based on the length ratios, which includes the proportion of the upper court to the three-dimensional face model, the proportion of the middle court to the three-dimensional face model, and the proportion of the lower court to the three-dimensional face model. Thus, the lengths of the three courts are based on the aligned three-dimensional face model, ensuring the accuracy of the determination of the three courts.

[0068] Of course, in other possible embodiments, the corrected 3D face model can also be used to meet the needs of other scenarios, which will not be elaborated here.

[0069] In summary, the three-dimensional face model alignment method of this disclosure, after aligning the three-dimensional face model according to the key points of the face, obtains relevant information in the corresponding scene based on the aligned three-dimensional face model, ensuring the accuracy of the obtained relevant information and improving the quality of meeting the needs of the relevant application scenarios.

[0070] To achieve the above embodiments, this disclosure also proposes a three-dimensional face model alignment processing device.

[0071] Figure 7 is a schematic diagram of a three-dimensional face model alignment processing device provided in an embodiment of this disclosure. This device can be implemented by software and / or hardware and is generally integrated into an electronic device for three-dimensional face model alignment processing. As shown in Figure 7, the device includes: a recognition module 710, a display module 720, a determination module 730, and an alignment module 740. The recognition module 710 is configured to, in response to a request for alignment of the three-dimensional face model, recognize multiple facial key points on the three-dimensional face model according to a preset recognition algorithm. The display module 720 is configured to display multiple facial key points on the three-dimensional face model. The determination module 730 is configured to, in response to a user's modification operation on at least one of the multiple facial key points, determine the modified multiple facial key points. The alignment module 740 is configured to align the three-dimensional face model based on the modified multiple facial key points.

[0072] The three-dimensional face model alignment processing device provided in this disclosure can execute the three-dimensional face model alignment processing method provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects of the method execution, which will not be described in detail here.

[0073] To implement the above embodiments, this disclosure also proposes a computer program product, including a computer program / instruction, which, when executed by a processor, implements the three-dimensional face model alignment processing method in the above embodiments.

[0074] Figure 8 is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure.

[0075] Referring specifically to Figure 8, which illustrates a structural schematic diagram suitable for implementing the electronic device 800 in the embodiments of this disclosure, the electronic device 800 in the embodiments of this disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. The electronic device shown in Figure 8 is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this disclosure.

[0076] As shown in Figure 8, the electronic device 800 may include a processor (e.g., a central processing unit, a graphics processing unit, etc.) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a memory 808 into a random access memory (RAM) 803. The RAM 803 also stores various programs and data required for the operation of the electronic device 800. The processor 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0077] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 807 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 808 including, for example, magnetic tapes, hard disks, etc.; and communication devices 809. Communication device 809 allows electronic device 800 to communicate wirelessly or wiredly with other devices to exchange data. Although FIG8 illustrates electronic device 800 with various devices, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0078] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 809, or installed from a memory 808, or installed from a ROM 802. When the computer program is executed by the processor 801, it performs the functions defined in the three-dimensional face model alignment processing method of embodiments of this disclosure.

[0079] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0080] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol), and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and end-to-end networks (e.g., ad hoc end-to-end networks), as well as any currently known or future-developed networks.

[0081] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0082] The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to:

[0083] In response to a request to align a 3D face model, multiple facial key points on the 3D face model are identified using a preset recognition algorithm, and these key points are displayed on the model. Then, in response to a user's modification of the facial key points, the modified key points are determined, and the 3D face model is aligned based on these modified key points. This technical solution combines a preset algorithm and user modifications to determine the target key points in the 3D face model, and aligns the model based on these target key points, thus improving alignment efficiency and ensuring alignment effectiveness.

[0084] Electronic devices can be programmed with computer program code in one or more programming languages ​​or combinations thereof to perform the operations of this disclosure. These programming languages ​​include, but are not limited to, object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0085] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0086] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0087] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0088] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0089] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0090] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0091] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims. Industrial applicability

[0092] The 3D face model alignment processing scheme disclosed herein responds to a request for alignment of the 3D face model by identifying multiple facial key points on the 3D face model according to a preset recognition algorithm, displaying these key points on the 3D face model, and then, responding to a user's modification operation on the facial key points, determining the modified key points, and aligning the 3D face model based on these modified key points. In this technical solution, the target key points in the 3D face model are determined by combining a preset algorithm and the user's modification operation, and the 3D face model is aligned based on these target key points. This not only improves alignment efficiency but also ensures alignment effectiveness, demonstrating strong industrial applicability.

Claims

1. A method for correcting a 3D human face model, wherein, Includes the following steps: In response to a request to align a 3D face model, multiple facial key points on the 3D face model are identified according to a preset recognition algorithm; Display the plurality of facial key points on the three-dimensional face model; In response to receiving a user's modification operation on at least one of the plurality of facial key points, the modified plurality of facial key points are determined; The 3D face model is aligned based on the modified multiple facial key points.

2. The method as described in claim 1, wherein, The steps for obtaining a user's modification operation on at least one of the plurality of facial key points include: In response to the user's selection of at least one of the plurality of facial key points; Obtain a movement operation on at least one facial key point corresponding to the selected operation.

3. The method as described in claim 1, wherein, The step of aligning the 3D face model based on the modified multiple facial key points includes: The modified multiple facial key points are divided into a first key point subset and a second key point subset; The orbitoauricular plane of the three-dimensional face model is determined based on the first subset of key points; The midsagittal plane of the 3D face model is determined based on the second subset of key points; The three-dimensional face model is aligned according to the orbitoauricular plane and the midsagittal plane.

4. The method of claim 3, wherein, The step of aligning the three-dimensional face model according to the orbitoauricular plane and the midsagittal plane includes: Determine the horizontal and vertical display surfaces corresponding to the preset display screen; The three-dimensional face model is aligned according to the horizontal display plane and the vertical display plane, wherein the orbitoauricular plane and the midsagittal plane of the aligned three-dimensional face model are located on the horizontal display plane and the vertical display plane, respectively.

5. The method as described in any one of claims 1-4, wherein, After aligning the 3D face model based on the modified multiple facial key points, the method further includes: Determine the front view of the face of the 3D face model after it has been aligned; In response to a request to obtain smile information, the mouth image region in the frontal view of the face is determined; The smile information corresponding to the request is identified based on the mouth image region.

6. The method of claim 5, wherein, When the smile information includes the smile line standard, the step of identifying the smile information corresponding to the acquisition request based on the mouth image region includes: Based on the mouth image region, identify the smile curve, the upper edge curve of the lower lip, and the smile cheek corridor; Determine the curve matching degree between the smile curve and the upper edge curve of the lower lip, and determine the cheek area of ​​the smile cheek corridor; The standard degree of the smile line is determined based on the curve matching degree and the cheek area.

7. The method as described in any one of claims 1-4, wherein, After aligning the 3D face model according to the modified multiple facial key points, the process further includes: In response to a request to acquire facial three-part information, multiple sets of three-part feature points in the corrected three-dimensional face model are identified, wherein each set of three-part feature points is located on the same plane perpendicular to the orbitoauricular plane of the three-dimensional face model; A reference plane parallel to the horizontal plane is generated based on each of the three court feature points to obtain multiple reference planes; The length and proportion of the three courts are obtained based on the planar distance between the multiple reference planes.

8. A device for aligning a three-dimensional human face model, wherein, include: The recognition module is configured to, in response to receiving a request to align a 3D face model, identify multiple facial key points on the 3D face model according to a preset recognition algorithm; The display module is configured to display the plurality of facial key points on the three-dimensional face model; The determination module is configured to determine the modified facial key points in response to receiving a user's modification operation on at least one of the plurality of facial key points. The alignment module is configured to align the 3D face model based on the modified multiple facial key points.

9. An electronic device, wherein, The electronic device includes: processor; A memory configured to store processor-executable instructions; The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the three-dimensional face model alignment processing method according to any one of claims 1-7.

10. A computer-readable storage medium, wherein, The computer-readable storage medium stores a computer program configured to perform the alignment processing method for a three-dimensional face model as described in any one of claims 1-7.

Images