A method for generating a virtual digital life

Abstract

The present invention relates to virtual reality, and specifically to a method for generating a virtual digital human. A target frontal head image is obtained; based on a preset base three-dimensional model, an initial three-dimensional model corresponding to the target frontal head image is generated; a series of facial actions are determined according to the publicity language, and a corresponding intermediate three-dimensional model is generated based on the initial three-dimensional model; an improved spherical linear interpolation method is used to perform interpolation processing on the initial three-dimensional model and the intermediate three-dimensional model to obtain multiple sets of interpolated three-dimensional coordinates; corresponding transition three-dimensional models are generated according to the multiple sets of interpolated three-dimensional coordinates, and a dynamic model sequence is generated in combination with the initial three-dimensional model and the intermediate three-dimensional model; a preset three-dimensional renderer is used to perform three-dimensional rendering on the dynamic model sequence to generate a video sequence; the technical solution provided by the present invention can effectively overcome the defects existing in the prior art that it is difficult to ensure the adaptation of the facial actions of the virtual digital human to the publicity language and the facial actions of the virtual digital human are difficult to transform smoothly.

Description

Technical Field

[0001] The present invention relates to virtual reality, and more particularly to a method for generating a virtual digital human. Background Art

[0002] With the rapid development of technology, virtual digital human technology has become a new favorite in corporate image promotion. A virtual digital human, as a virtual character image constructed by the most advanced computer technology, can simulate human appearance, voice, movements and behaviors, and even can perform self-learning through artificial intelligence technology, providing a more realistic and intelligent experience.

[0003] The development of virtual digital human technology not only enriches the ways of corporate image promotion, but also brings unprecedented marketing opportunities to enterprises. The application of virtual digital humans in corporate image promotion is very extensive, including brand ambassadors, virtual customer service, virtual lecturers, etc. As a brand ambassador, a virtual digital human can create a more charming brand image for an enterprise and attract the attention of consumers.

[0004] Although virtual digital human technology shows great potential in corporate image promotion, it still faces some technical challenges. For example, how to ensure the adaptation of the facial movements of the virtual digital human to the promotional language, how to make the facial movements of the virtual digital human change more smoothly, and effectively improve the realism, etc. In the future, virtual digital human technology will play a more important role in corporate image promotion and bring greater commercial value to enterprises. Summary of the Invention

[0005] (I) Technical Problems to be Solved

[0006] In view of the above-mentioned drawbacks of the prior art, the present invention provides a method for generating a virtual digital human, which can effectively overcome the defects of the prior art that it is difficult to ensure the adaptation of the facial movements of the virtual digital human to the promotional language and the facial movements of the virtual digital human are difficult to change smoothly.

[0007] (II) Technical Solutions

[0008] To achieve the above object, the present invention is realized through the following technical solutions:

[0009] A method for generating a virtual digital human, comprising the following steps:

[0010] S1. Obtain a target frontal head image;

[0011] S2. Generate an initial 3D model corresponding to the target frontal head image based on a preset base 3D model;

[0012] S3. Determine a series of facial movements according to the promotional language, and generate a corresponding intermediate 3D model based on the initial 3D model;

[0013] S4. Use an improved spherical linear interpolation method to perform interpolation processing on the initial three-dimensional model and the intermediate three-dimensional model to obtain multiple sets of interpolated three-dimensional coordinates;

[0014] S5. Generate corresponding transitional three-dimensional models according to multiple sets of interpolated three-dimensional coordinates, and generate a dynamic model sequence in combination with the initial three-dimensional model and the intermediate three-dimensional model;

[0015] S6. Use a preset three-dimensional renderer to perform three-dimensional rendering on the dynamic model sequence to generate a video sequence;

[0016] Among them, in the improved spherical linear interpolation method, on the one hand, by introducing an included angle threshold and using a non-linear interpolation method to deal with the situation where the included angle approaches 0, and on the other hand, by optimizing the parameters of the spherical linear interpolation to avoid calculating complex trigonometric functions, so as to improve the calculation efficiency.

[0017] Preferably, in S2, based on the preset base three-dimensional model, generating the initial three-dimensional model corresponding to the target frontal head image includes:

[0018] S21. Generate the contour three-dimensional model data of the target frontal head image according to the target frontal head image and the base three-dimensional model;

[0019] S22. Align the organs in the target frontal head image to generate the organ three-dimensional model data of the target frontal head image;

[0020] S23. Perform fusion processing on the contour three-dimensional model data and the organ three-dimensional model data to generate the initial three-dimensional model corresponding to the target frontal head image.

[0021] Preferably, in S21, generating the contour three-dimensional model data of the target frontal head image according to the target frontal head image and the base three-dimensional model includes:

[0022] S211. Extract the first feature points in the target frontal head image, and determine the second feature points corresponding to the first feature points in the base three-dimensional model;

[0023] S212. Generate the contour three-dimensional model data of the target frontal head image according to the first feature points and the second feature points.

[0024] Preferably, in S212, generating the contour three-dimensional model data of the target frontal head image according to the first feature points and the second feature points includes:

[0025] S2121. Align the base three-dimensional model and the target frontal head image according to the first feature points and the second feature points to obtain the aligned base three-dimensional model;

[0026] S2122. Use radial basis functions to interpolate the aligned base three-dimensional model to generate the contour three-dimensional model data of the target frontal head image.

[0027] Preferably, in S3, a series of facial actions are determined according to the promotional language, and the corresponding intermediate three-dimensional models are generated based on the initial three-dimensional model, including:

[0028] Determine a series of facial actions according to the language text and language emotion of the promotional language, and complete the mapping of each facial action on the initial three-dimensional model to generate the corresponding intermediate three-dimensional model.

[0029] Preferably, in S4, an improved spherical linear interpolation method is used to interpolate the initial three-dimensional model and the intermediate three-dimensional model to obtain multiple sets of interpolated three-dimensional coordinates, including:

[0030] S41. Preprocess the initial three-dimensional model and the intermediate three-dimensional model;

[0031] S42. Extract a set of feature points from each three-dimensional model, and use a feature point matching algorithm to determine the corresponding relationship of the feature points between two adjacent three-dimensional models;

[0032] S43. Map the feature points of each matched three-dimensional model to a high-dimensional unit sphere to convert the feature point coordinates into a corresponding set of intermediate unit vectors;

[0033] S44. Select a series of interpolation points in the spherical space between two adjacent three-dimensional models and obtain multiple sets of transitional unit vectors;

[0034] S45. Based on the intermediate unit vectors and the transitional unit vectors, use the improved spherical linear interpolation method to perform interpolation calculations on two adjacent three-dimensional models to obtain multiple sets of interpolated unit vectors;

[0035] S46. Convert the multiple sets of interpolated unit vectors into the corresponding interpolated three-dimensional coordinates;

[0036] S47. Repeat S44 - S46 until the interpolation calculations for the last two intermediate three-dimensional models are completed to obtain multiple sets of interpolated three-dimensional coordinates.

[0037] Preferably, the preprocessing of the initial three-dimensional model and the intermediate three-dimensional model in S41 includes:

[0038] Perform preprocessing operations on the initial three-dimensional model and the intermediate three-dimensional model, including noise removal, surface smoothing, and size standardization.

[0039] Preferably, in S45, based on the intermediate unit vectors and the transitional unit vectors, use the improved spherical linear interpolation method to perform interpolation calculations on two adjacent three-dimensional models to obtain multiple sets of interpolated unit vectors, including:

[0040] S451. Select two adjacent intermediate unit vectors and the first set of transitional unit vectors therebetween, and use the corresponding unit vectors in the previous set of intermediate unit vectors and the first set of transitional unit vectors as the starting unit vector and the target unit vector, respectively;

[0041] S452. Perform interpolation calculation on the starting unit vector and the target unit vector by using an improved spherical linear interpolation formula to obtain an interpolated unit vector;

[0042] S453. Repeat S451 - S452 until the interpolation calculation for the last pair of corresponding unit vectors in the previous set of intermediate unit vectors and the first set of transitional unit vectors is completed;

[0043] S454. Repeat S451 - S453 until the interpolation calculation for the last pair of corresponding unit vectors in the last set of transitional unit vectors and the next set of intermediate unit vectors is completed, to obtain multiple sets of interpolated unit vectors.

[0044] Preferably, in S452, performing interpolation calculation on the starting unit vector and the target unit vector by using an improved spherical linear interpolation formula to obtain an interpolated unit vector includes:

[0045] Based on dealing with the case where the included angle approaches 0 by introducing an included - angle threshold and adopting a non - linear interpolation method, and optimizing the parameters of the spherical linear interpolation to avoid calculating complex trigonometric functions to improve the calculation efficiency, the spherical linear interpolation formula is improved:

[0046]

[0047] where Slerp(q 0 , q 1 ) is the calculated interpolated unit vector, q 0 is the starting unit vector, q 1 is the target unit vector, θ is the included angle between the starting unit vector q 0 and the target unit vector q 1 , ε is the included - angle threshold, t is the interpolation parameter, and 0 ≤ t ≤ 1.

[0048] Preferably, in S5, generating corresponding transitional 3D models according to multiple sets of interpolated 3D coordinates and generating a dynamic model sequence by combining the initial 3D model and the intermediate 3D model includes:

[0049] Generate corresponding transitional 3D models according to multiple sets of interpolated 3D coordinates, and insert the transitional 3D models at the corresponding positions between the initial 3D model and the intermediate 3D model, and between the intermediate 3D models to generate a dynamic model sequence.

[0050] (III) Beneficial Effects

[0051] Compared with the prior art, a virtual digital human generation method provided by the present invention has the following beneficial effects:

[0052] 1) According to the target frontal head image and the base three-dimensional model, generate the contour three-dimensional model data of the target frontal head image, align the organs in the target frontal head image to generate the organ three-dimensional model data of the target frontal head image, perform fusion processing on the contour three-dimensional model data and the organ three-dimensional model data to generate the initial three-dimensional model corresponding to the target frontal head image, determine a series of facial actions according to the language text and language emotion of the publicity language, and complete the mapping of each facial action on the initial three-dimensional model to generate the corresponding intermediate three-dimensional model, so as to ensure that the intermediate three-dimensional model has facial actions adapted to the language text and language emotion of the publicity language, effectively improve the viewing experience of viewers, help enterprises create a more charming brand image, and attract the attention of consumers;

[0053] 2) Use the improved spherical linear interpolation method to perform interpolation processing on the initial three-dimensional model and the intermediate three-dimensional model to obtain multiple groups of interpolated three-dimensional coordinates, generate the corresponding transition three-dimensional models according to the multiple groups of interpolated three-dimensional coordinates, and generate a dynamic model sequence in combination with the initial three-dimensional model and the intermediate three-dimensional model. Use the preset three-dimensional renderer to perform three-dimensional rendering on the dynamic model sequence to generate a video sequence. The improved spherical linear interpolation method can make the virtual digital human transform smoothly between two adjacent intermediate three-dimensional models, effectively improve the realism, further enhance the viewing experience of viewers, play a more important role in corporate image publicity, and bring greater commercial value to enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0055] Figure 1 It is a flowchart of the present invention;

[0056] Figure 2 It is a flowchart of generating the initial three-dimensional model corresponding to the target frontal head image in the present invention;

[0057] Figure 3 It is a flowchart of generating a dynamic model sequence by using the improved spherical linear interpolation method in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0058] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0059] A method for generating a virtual digital human, as Figure 1 shown, S1, obtain a target frontal head image.

[0060] S2, based on a preset base three-dimensional model, generate an initial three-dimensional model corresponding to the target frontal head image, as Figure 2 shown, specifically including:

[0061] S21, generate contour three-dimensional model data of the target frontal head image according to the target frontal head image and the base three-dimensional model;

[0062] S22, perform alignment processing on the organs in the target frontal head image to generate organ three-dimensional model data of the target frontal head image;

[0063] S23, perform fusion processing on the contour three-dimensional model data and the organ three-dimensional model data to generate an initial three-dimensional model corresponding to the target frontal head image.

[0064] Specifically, in S21, generate contour three-dimensional model data of the target frontal head image according to the target frontal head image and the base three-dimensional model, as Figure 2 shown, including:

[0065] S211, extract the first feature points in the target frontal head image, and determine the second feature points corresponding to the first feature points in the base three-dimensional model;

[0066] S212, generate contour three-dimensional model data of the target frontal head image according to the first feature points and the second feature points.

[0067] Specifically, in S212, generate contour three-dimensional model data of the target frontal head image according to the first feature points and the second feature points, as Figure 2 shown, including:

[0068] S2121, perform alignment processing on the base three-dimensional model and the target frontal head image according to the first feature points and the second feature points to obtain an aligned base three-dimensional model;

[0069] S2122. Use a radial basis function to perform interpolation on the aligned base three-dimensional model to generate the contour three-dimensional model data of the target frontal head image.

[0070] S3. Determine a series of facial actions according to the promotional language, and generate corresponding intermediate three-dimensional models based on the initial three-dimensional model, specifically including:

[0071] Determine a series of facial actions according to the language text and language emotion of the promotional language, and complete the mapping of each facial action on the initial three-dimensional model to generate the corresponding intermediate three-dimensional model.

[0072] In the above technical solution, according to the target frontal head image and the base three-dimensional model, generate the contour three-dimensional model data of the target frontal head image, perform alignment processing on the organs in the target frontal head image to generate the organ three-dimensional model data of the target frontal head image, perform fusion processing on the contour three-dimensional model data and the organ three-dimensional model data to generate the initial three-dimensional model corresponding to the target frontal head image, determine a series of facial actions according to the language text and language emotion of the promotional language, and complete the mapping of each facial action on the initial three-dimensional model to generate the corresponding intermediate three-dimensional model, so as to ensure that the intermediate three-dimensional model has facial actions adapted to the language text and language emotion of the promotional language, effectively improve the viewing experience of the viewer, help the enterprise create a more charming brand image, and attract the attention of consumers.

[0073] S4. Use an improved spherical linear interpolation method to perform interpolation on the initial three-dimensional model and the intermediate three-dimensional model to obtain multiple sets of interpolated three-dimensional coordinates, as Figure 3 shown, specifically including:

[0074] S41. Preprocess the initial three-dimensional model and the intermediate three-dimensional model;

[0075] S42. Extract a set of feature points from each three-dimensional model, and use a feature point matching algorithm to determine the corresponding relationship of feature points between adjacent two three-dimensional models;

[0076] S43. Map the feature points of each matched three-dimensional model to a high-dimensional unit sphere to convert the feature point coordinates into a corresponding set of intermediate unit vectors;

[0077] S44. Select a series of interpolation points in the spherical space between adjacent two three-dimensional models, and obtain multiple sets of transition unit vectors;

[0078] S45. Based on the intermediate unit vectors and the transition unit vectors, use the improved spherical linear interpolation method to perform interpolation calculation on adjacent two three-dimensional models to obtain multiple sets of interpolated unit vectors;

[0079] S46. Convert multiple groups of interpolation unit vectors into corresponding interpolation three-dimensional coordinates;

[0080] S47. Repeat S44 - S46 until the interpolation calculation of the last two intermediate three-dimensional models is completed, obtaining multiple groups of interpolation three-dimensional coordinates.

[0081] In the technical solution of this application, for the improved spherical linear interpolation method: on the one hand, by introducing an angle threshold and using a non-linear interpolation method to deal with the situation where the angle approaches 0; on the other hand, by optimizing the parameters of the spherical linear interpolation to avoid calculating complex trigonometric functions, so as to improve the calculation efficiency.

[0082] 1) In S41, preprocess the initial three-dimensional model and the intermediate three-dimensional model, as Figure 3 shown, including:

[0083] Perform preprocessing operations on the initial three-dimensional model and the intermediate three-dimensional model, including removing noise, smoothing the surface, and standardizing the size.

[0084] 2) In S45, based on the intermediate unit vectors and the transition unit vectors, use the improved spherical linear interpolation method to perform interpolation calculation on two adjacent three-dimensional models, obtaining multiple groups of interpolation unit vectors, including:

[0085] S451. Select two adjacent groups of intermediate unit vectors and the first group of transition unit vectors between them, and use the unit vectors with corresponding relationships in the previous group of intermediate unit vectors and the first group of transition unit vectors as the starting unit vector and the target unit vector respectively;

[0086] S452. Use the improved spherical linear interpolation formula to perform interpolation calculation on the starting unit vector and the target unit vector, obtaining an interpolation unit vector;

[0087] S453. Repeat S451 - S452 until the interpolation calculation of the last pair of unit vectors with corresponding relationships in the previous group of intermediate unit vectors and the first group of transition unit vectors is completed;

[0088] S454. Repeat S451 - S453 until the interpolation calculation of the last pair of unit vectors with corresponding relationships in the last group of transition unit vectors and the next group of intermediate unit vectors is completed, obtaining multiple groups of interpolation unit vectors.

[0089] Specifically, in S452, use the improved spherical linear interpolation formula to perform interpolation calculation on the starting unit vector and the target unit vector, obtaining an interpolation unit vector, including:

[0090] By introducing an included angle threshold and using a non - linear interpolation method to deal with the situation where the included angle approaches 0, and by optimizing the parameters of spherical linear interpolation to avoid calculating complex trigonometric functions, the calculation efficiency is improved, and the spherical linear interpolation formula is improved as follows:

[0091]

[0092] Among them, Slerp(q 0 ,q 1 ) is the calculated interpolation unit vector, q 0 is the starting unit vector, q 1 is the target unit vector, θ is the included angle between the starting unit vector q 0 and the target unit vector q 1 , ε is the included angle threshold, t is the interpolation parameter, and 0 ≤ t ≤ 1.

[0093] S5. Generate corresponding transitional 3D models based on multiple groups of interpolated 3D coordinates, and generate a dynamic model sequence in combination with the initial 3D model and the intermediate 3D model, as Figure 3 shown, specifically including:

[0094] Generate corresponding transitional 3D models based on multiple groups of interpolated 3D coordinates, and insert the transitional 3D models at the corresponding positions between the initial 3D model and the intermediate 3D model, and between the intermediate 3D models to generate a dynamic model sequence.

[0095] S6. Use a preset 3D renderer to perform 3D rendering on the dynamic model sequence to generate a video sequence.

[0096] In the above technical solution, an improved spherical linear interpolation method is used to perform interpolation processing on the initial 3D model and the intermediate 3D model to obtain multiple groups of interpolated 3D coordinates. Corresponding transitional 3D models are generated based on the multiple groups of interpolated 3D coordinates, and a dynamic model sequence is generated in combination with the initial 3D model and the intermediate 3D model. A preset 3D renderer is used to perform 3D rendering on the dynamic model sequence to generate a video sequence. Using the improved spherical linear interpolation method can enable the virtual digital human to transform smoothly between two adjacent intermediate 3D models, effectively improve the fidelity, further enhance the viewer's perception, play a more important role in corporate image promotion, and bring greater commercial value to the enterprise.

[0097] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for generating a virtual digital human, characterized in that: The following steps are involved: S1, obtain the frontal image of the target head; S2, generating an initial three-dimensional model corresponding to the frontal image of the target head based on a preset base three-dimensional model; S3, determining a series of facial movements according to the promotional language, and generating a corresponding intermediate three-dimensional model based on the initial three-dimensional model; S4, using an improved spherical linear interpolation method to interpolate the initial three-dimensional model and the intermediate three-dimensional model to obtain multiple sets of interpolated three-dimensional coordinates; S5, generating corresponding transitional three-dimensional models according to the multiple sets of interpolated three-dimensional coordinates, and generating a dynamic model sequence by combining the initial three-dimensional model and the intermediate three-dimensional model; S6, using a preset 3D renderer to perform 3D rendering on the dynamic model sequence to generate a video sequence; Among them, in the improved spherical linear interpolation method, on the one hand, an angle threshold is introduced and a nonlinear interpolation method is used to deal with the situation where the angle approaches 0. On the other hand, the calculation efficiency is improved by optimizing the parameters of the spherical linear interpolation to avoid calculating complex trigonometric functions. In S4, an improved spherical linear interpolation method is used to interpolate the initial 3D model and the intermediate 3D model to obtain multiple sets of interpolated 3D coordinates, including: S41, preprocessing the initial three-dimensional model and the intermediate three-dimensional model; S42, extracting a set of feature points from each three-dimensional model, and using a feature point matching algorithm to determine the corresponding relationship between the feature points of two adjacent three-dimensional models; S43, mapping the matched feature points of each three-dimensional model onto a high-dimensional unit sphere to convert the feature point coordinates into a corresponding set of intermediate unit vectors; S44, selecting a series of interpolation points in the spherical space between two adjacent three-dimensional models, and obtaining multiple groups of transition unit vectors; S45, based on the intermediate unit vector and the transition unit vector, using an improved spherical linear interpolation method to perform interpolation calculation on two adjacent three-dimensional models to obtain multiple groups of interpolation unit vectors; S46, converting multiple groups of interpolation unit vectors into corresponding interpolation three-dimensional coordinates; S47, repeat S44 to S46 until the interpolation calculation of the last two intermediate three-dimensional models is completed to obtain multiple sets of interpolation three-dimensional coordinates; In S45, based on the intermediate unit vector and the transition unit vector, an improved spherical linear interpolation method is used to perform interpolation calculations on two adjacent three-dimensional models to obtain multiple groups of interpolation unit vectors, including: S451, selecting two adjacent groups of intermediate unit vectors and the first group of transition unit vectors therebetween, and using the corresponding unit vectors in the first group of intermediate unit vectors and the first group of transition unit vectors as the starting unit vector and the target unit vector, respectively; S452, using an improved spherical linear interpolation formula to perform interpolation calculation on the starting unit vector and the target unit vector to obtain an interpolation unit vector; S453, repeat S451 to S452 until the interpolation calculation of the last pair of unit vectors in the corresponding relationship between the previous group of intermediate unit vectors and the first group of transition unit vectors is completed; S454, repeat S451 to S453 until the interpolation calculation of the last set of transition unit vectors and the last pair of corresponding unit vectors in the next set of intermediate unit vectors is completed, and multiple sets of interpolation unit vectors are obtained; In S452, the improved spherical linear interpolation formula is used to interpolate the starting unit vector and the target unit vector to obtain the interpolation unit vector, including: The spherical linear interpolation formula is improved by introducing an angle threshold and using a nonlinear interpolation method to deal with the situation where the angle approaches 0, and by optimizing the parameters of the spherical linear interpolation to avoid calculating complex trigonometric functions to improve the calculation efficiency: Among them, Slerp(q0,q1) is the calculated interpolation unit vector, q0 is the starting unit vector, q1 is the target unit vector, θ is the angle between the starting unit vector q0 and the target unit vector q1, ε is the angle threshold, t is the interpolation parameter, 0≤t≤1.

2. The method for generating a virtual digital human according to claim 1, characterized in that: In S2, based on the preset base three-dimensional model, an initial three-dimensional model corresponding to the frontal image of the target head is generated, including: S21, generating contour three-dimensional model data of the target head front image according to the target head front image and the base three-dimensional model; S22, performing alignment processing on the organs in the target head front image to generate three-dimensional model data of the organs in the target head front image; S23, fusing the contour three-dimensional model data and the organ three-dimensional model data to generate an initial three-dimensional model corresponding to the target head frontal image.

3. The method for generating a virtual digital human according to claim 2, characterized in that: In S21, the contour three-dimensional model data of the front image of the target head is generated according to the front image of the target head and the base three-dimensional model, including: S211, extracting a first feature point in the front image of the target head, and determining a second feature point corresponding to the first feature point in the base three-dimensional model; S212: Generate contour three-dimensional model data of the target head frontal image based on the first feature point and the second feature point.

4. The method for generating a virtual digital human according to claim 3, characterized in that: In S212, the contour three-dimensional model data of the target head front image is generated according to the first feature point and the second feature point, including: S2121, aligning the base three-dimensional model with the target head front image according to the first feature point and the second feature point to obtain an aligned base three-dimensional model; S2122, using radial basis functions to perform interpolation processing on the aligned base three-dimensional model to generate contour three-dimensional model data of the target head frontal image.

5. The method for generating a virtual digital human according to claim 1, characterized in that: In S3, a series of facial actions are determined according to the promotional language, and a corresponding intermediate 3D model is generated based on the initial 3D model, including: A series of facial movements are determined according to the language text and language emotion of the propaganda language, and the mapping of each facial movement is completed on the initial three-dimensional model to generate a corresponding intermediate three-dimensional model.

6. The method for generating a virtual digital human according to claim 1, characterized in that: In S41, the initial 3D model and the intermediate 3D model are preprocessed, including: The initial 3D model and the intermediate 3D model are preprocessed including noise removal, surface smoothing and size standardization.

7. The method for generating a virtual digital human according to claim 1, characterized in that: In S5, a corresponding transitional three-dimensional model is generated according to multiple sets of interpolated three-dimensional coordinates, and a dynamic model sequence is generated by combining the initial three-dimensional model and the intermediate three-dimensional model, including: Corresponding transitional three-dimensional models are generated according to multiple sets of interpolated three-dimensional coordinates, and the transitional three-dimensional models are inserted into corresponding positions between the initial three-dimensional model and the intermediate three-dimensional model, and the intermediate three-dimensional models, to generate a dynamic model sequence.

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