VR virtual display method and system for cultural and creative products

Abstract

The invention discloses a VR virtual display method and system for cultural and creative products, and relates to the technical field of virtual reality display, and the method comprises the following components: S1, a data collection and analysis step, S2, a VR scene construction step, S3, an interaction and rendering step, and S4, an emotional resonance monitoring and feedback step. According to the method, the related data of the cultural and creative products are comprehensively collected, and the emotion database is constructed by adopting the emotion venation mining algorithm, so that accurate capture and deep analysis of the emotion of the cultural and creative products are realized, the virtual display effect of the cultural and creative products is improved, a user can deeply experience the emotion connotation of the products in a VR scene, and the user experience is improved. The emotion experience and resonance of the user are enhanced, through construction and application of the emotion database, richer and finer emotion expression means are provided for virtual display of cultural and creative products, and the display content is more vivid and interesting.

Description

Technical Field

[0001] The present invention relates to the field of virtual reality display technology, and in particular to a method and system for VR virtual display of cultural and creative products. Background Art

[0002] With the rapid development of virtual reality (VR) technology, its application in the field of cultural and creative product display is becoming more and more extensive. As the crystallization of culture and creativity, cultural and creative products are rich in connotation and unique in emotional expression. Traditional display methods are difficult to fully demonstrate their charm. Therefore, using VR technology for virtual display of cultural and creative products has become a new trend. Through VR technology, users can experience the charm of cultural and creative products in an immersive way and enhance their emotional experience and resonance.

[0003] In the traditional VR scene construction steps, the integration of emotional elements of cultural and creative products and the creation of emotional atmosphere of the scene are often neglected. The scene layout and element design lack specificity and cannot accurately convey the emotional connotation of cultural and creative products. At the same time, the music and special effects elements in traditional VR displays also lack relevance to the emotional characteristics of cultural and creative products, making the overall display effect monotonous and boring, making it difficult to attract users' attention and stimulate their emotional resonance.

[0004] To sum up, the existing technology has obvious shortcomings and cannot meet the users' demand for deep experience of the emotional connotation of cultural and creative products. Therefore, it is particularly important to develop a VR virtual display method and system for cultural and creative products. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the existing technology and provide a VR virtual display method and system for cultural and creative products. It can comprehensively collect relevant data of cultural and creative products and use emotional context mining algorithms to build an emotional database, thereby providing richer and more delicate emotional expression means for the virtual display of cultural and creative products, thereby enhancing the user's emotional experience and resonance.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a VR virtual display method for cultural and creative products, the specific steps of which are:

[0007] S1, data collection and analysis steps: Comprehensively collect data related to cultural and creative products, including social economic data, cultural trend data, creator social network data, and evolution data of cultural and creative products in different historical periods during the birth period of cultural and creative products, and use the emotional context mining algorithm to build an emotional database. The algorithm formula is: Where E db represents the comprehensive emotional index of the emotional database, n is the number of data categories, X i represents the i-th type of data, M iis the multi-dimensional feature mapping function for the i-th type of data, σ i is the weight parameter of the i-th category data, Y represents the creator’s social network data, N is the sentiment propagation function of the social network data, and ρ is the weight of the creator’s social network data;

[0008] S2, VR scene construction steps: construct a hyper-realistic VR display scene based on the emotion database, and use the scene layout algorithm based on spatial emotion distribution to divide the scene into multiple emotion areas. The formula is: Among them, A j represents the area of ​​the jth emotional region, m is the number of emotional categories, E j represents the intensity value of the j-th emotion in the emotion database, ω j is the spatial influence weight of the jth emotion, S represents the total area of ​​the entire VR scene, and characters closely connected with cultural and creative products are set in each emotional area. The emotional expression actions of the characters are based on the emotion-driven action generation algorithm, which is: Among them A c represents the character's action amplitude and frequency parameters, p is the number of influencing factors, R l Indicates the role positioning information of the role, E r Indicates the sentiment value of the sentiment area, B l is the action generation function for the lth influencing factor, μ l is the weight of the lth influencing factor;

[0009] S3, interaction and rendering steps: realize the deep interaction between users and characters in VR scenes, use brain-computer interface technology to capture users' thinking intention information, and interact with characters based on emotional resonance. Music rendering uses emotional dynamic music generation algorithm to generate music in real time according to the emotional characteristics of cultural and creative products and the interactive emotional state of users in VR scenes. The formula is: Among them, M g represents the musical note sequence, rhythm and harmony parameter set, r is the number of factors that affect the generation of music, I u Indicates the emotional intensity of the user's thinking intention feedback through the brain-computer interface, E s Indicates the emotional atmosphere intensity of the current VR scene, T m Represents the core emotional theme vector of cultural and creative products, C q is the music generating function for the qth influencing factor, ξ q is the weight of the qth influencing factor;

[0010] S4, emotional resonance monitoring and feedback step: monitor the user's emotional resonance state, use multimodal biosensors to collect user physiological data and behavioral data, and judge the degree of emotional resonance by integrating the emotion recognition algorithm. The algorithm formula is: Where R em represents the quantitative value of emotional resonance, u is the number of combined types of physiological and behavioral data, and B t represents the physiological data collected by the t-th biosensor, V t represents the t-th behavior data, P t is the emotion mapping function for the t-th combination of physiological and behavioral data, λ t is the weight of the tth combination of physiological and behavioral data, Z represents the user's overall interaction history data in the VR scene, W is the emotional tendency function of the interaction history data, φ is the weight of the interaction history data, and provides personalized feedback information based on the emotional resonance monitoring results, recommends cultural and creative products that are deeply in line with the user's emotional resonance points, and provides inspirational materials for the creation of cultural and creative products based on the user's emotional resonance path.

[0011] Furthermore, in the data collection and analysis step, the collection of cultural trend data not only covers mainstream cultural trends, but also deeply explores niche cultural schools and regional cultural trend information, and extracts unique emotional semantic labels through cultural semantic analysis algorithms. The algorithm formula is: Where L s represents the set of sentiment semantic labels, w is the number of cultural trend text fragments, K v represents the vth cultural trend text segment, D v is the semantic parsing function of the vth text segment, θ v is the weight coefficient of the vth text segment.

[0012] Furthermore, in the VR scene construction step, when the scene is constructed, the weather effect simulation in the scene is dynamically adjusted according to the emotional rhythm information in the emotional database. For cultural and creative products that express passionate emotions and have a fast emotional rhythm, the weather effects are mainly violent storms, lightning and thunder, and the weather change frequency formula is: Among them, F w Indicates the frequency of weather changes, E p represents the emotional rhythm intensity value, α and β are adjustment coefficients, E j Focusing on the spatial emotional area division, E p Focus on the impact of emotional rhythm on weather effects.

[0013] Furthermore, in the interaction and rendering step, in terms of the interaction between the user and the character through the brain-computer interface, the character's response content generation adopts a text generation algorithm based on emotional logic reasoning. The algorithm constructs the response text according to the user's thinking intention emotion, the scene emotional logic and the character's own emotional personality. The specific calculation method is: Where T rrepresents the semantic structure and vocabulary selection parameters of the response text, y is the number of influencing factors, I u Indicates the user’s thinking intention and emotional information, S l Represents the scene emotional logic information, R p Indicates the character's emotional personality information, F x is the text generation function for the xth influencing factor, ∈ x is the weight coefficient of the xth influencing factor.

[0014] Furthermore, in the emotional resonance monitoring and feedback step, when using a multimodal biosensor to collect data, a filtering algorithm based on emotion feature optimization is used for data preprocessing. When the user is in a scene interaction with complex and changeable emotions, the algorithm performs targeted filtering on the collected data according to the emotion classification model in the emotion database. The filter parameter adjustment formula is: Among them G f represents the filtering parameters, E c It represents the emotional complexity value of the current scene, γ and δ are adjustment coefficients. If it is found that more refined filtering is required in high emotional complexity scenes and high data accuracy is required, then γ = 0.7 and δ = 0.3.

[0015] Furthermore, in the VR scene construction step, the rendering of special effect elements in the scene is dynamically triggered and the intensity is adjusted according to the emotion peak information in the emotion database. For cultural and creative products with strong emotional burst points, the brightness and density of the special effect elements are greatly improved at the emotional peak moment. The special effect intensity adjustment formula is: Among them I e Indicates the strength of the special effect, E b It represents the peak intensity value of emotion, η and θ are conversion coefficients. If it is found that the high emotion peak has high requirements on the special effect intensity and presents a nonlinear relationship, then η=0.8, θ=0.2.

[0016] Furthermore, in the interaction and rendering step, the instrument timbre of the music is dynamically switched according to the user's emotional experience trend in the VR scene during music rendering. When the user's emotional experience changes from calm to excited, the instrument timbre switches from soft string music to passionate brass music. The timbre switching threshold formula is: Where T s Indicates the tone switching threshold, E t It represents the intensity of the user's emotional experience trend, κ and λ are the threshold adjustment coefficients. If it is found that the intensity of the emotional experience trend has a greater impact on the timbre switching and the threshold needs to be sensitively adjusted during rapid changes, then κ=0.75, λ=0.25.

[0017] Furthermore, in the emotional resonance monitoring and feedback step, in order to provide personalized feedback information, a virtual cultural and creative community recommendation is also constructed based on the user's emotional resonance characteristics. If the user has a strong resonance with a certain emotional element and has a social tendency, the system recommends a virtual cultural and creative community to the user through a community matching algorithm based on the user's emotional resonance point, social behavior data, and the cultural atmosphere characteristics of the cultural and creative community. The algorithm formula is: Among them C m represents the recommendation list of virtual cultural and creative communities, a is the number of factors that affect community matching, and E z is the community matching function for the zth factor, R e m represents the quantitative value of the user's emotional resonance, U b Represents user social behavior data, C a Represents the cultural atmosphere feature vector of the cultural and creative community, ω z is the weight coefficient of the zth factor. If the user's emotional resonance information has a greater impact on community matching and accounts for 35%, then ω1 = 0.35.

[0018] Furthermore, in the data collection and analysis step, the evolution data of cultural and creative products in different historical periods are collected, including the collection of information on the changes in design styles, usage scenarios, and audience groups in different eras, and the emotional evolution trajectory is extracted through the evolution trend analysis algorithm. The algorithm formula is: Where T ev represents the parameter set of emotion evolution trajectory, c is the number of evolution data categories, H b represents the b-th type of evolution data, G b is the trend analysis function of the b-th type of evolution data, τ b The weight coefficients for the b-th type of evolved data are intended to quantify the relative importance of different data types in a specific sentiment analysis or construction process, so as to accurately extract the sentiment information related to cultural and creative products.

[0019] On the other hand, a VR virtual display system for cultural and creative products is characterized in that the system includes a data collection and analysis module, a VR scene construction module, an interaction and rendering module, and an emotional resonance monitoring and feedback module:

[0020] The data collection and analysis module: comprehensively collects data related to cultural and creative products, including social economic data, cultural trend data, creator social network data, and evolution data of cultural and creative products in different historical periods during the birth period of cultural and creative products, and uses the emotional context mining algorithm to build an emotional database. The algorithm formula is: Where E db represents the comprehensive emotional index of the emotional database, n is the number of data categories, X irepresents the i-th type of data, M i is the multi-dimensional feature mapping function for the i-th type of data, σ i is the weight parameter of the i-th category data, Y represents the creator’s social network data, N is the sentiment propagation function of the social network data, and ρ is the weight of the creator’s social network data;

[0021] The VR scene construction module: constructs a hyper-realistic VR display scene based on the emotion database, and uses a scene layout algorithm based on spatial emotion distribution to divide the scene into multiple emotion areas. The formula is: Among them, A j represents the area of ​​the jth emotional region, m is the number of emotional categories, E j represents the intensity value of the j-th emotion in the emotion database, ω j is the spatial influence weight of the jth emotion, S represents the total area of ​​the entire VR scene, and characters closely connected with cultural and creative products are set in each emotional area. The emotional expression actions of the characters are based on the emotion-driven action generation algorithm, which is: Among them A c represents the character's action amplitude and frequency parameters, p is the number of influencing factors, R l Indicates the role positioning information of the role, E r Indicates the sentiment value of the sentiment area, B l is the action generation function for the lth influencing factor, μ l is the weight of the lth influencing factor;

[0022] The interaction and rendering module: realizes the deep interaction between the user and the character in the VR scene, uses the brain-computer interface technology to capture the user's thinking intention information, and interacts with the character based on emotional resonance. The music rendering adopts the emotional dynamic music generation algorithm to generate music in real time according to the emotional characteristics of the cultural and creative products and the interactive emotional state of the user in the VR scene. The formula is: Among them, M g represents the musical note sequence, rhythm and harmony parameter set, r is the number of factors that affect the generation of music, I u Indicates the emotional intensity of the user's thinking intention feedback through the brain-computer interface, E s Indicates the emotional atmosphere intensity of the current VR scene, T m Represents the core emotional theme vector of cultural and creative products, C q is the music generating function for the qth influencing factor, ξ q is the weight of the qth influencing factor;

[0023] The emotional resonance monitoring and feedback module: monitors the user's emotional resonance state, collects the user's physiological data and behavioral data using multimodal biosensors, and determines the degree of emotional resonance by integrating the emotion recognition algorithm. The algorithm formula is: Where R em represents the quantitative value of emotional resonance, u is the number of combined types of physiological and behavioral data, and B t represents the physiological data collected by the t-th biosensor, V t represents the t-th behavior data, P t is the emotion mapping function for the t-th combination of physiological and behavioral data, λ t is the weight of the tth combination of physiological and behavioral data, Z represents the user's overall interaction history data in the VR scene, W is the emotional tendency function of the interaction history data, φ is the weight of the interaction history data, and provides personalized feedback information based on the emotional resonance monitoring results, recommends cultural and creative products that are deeply in line with the user's emotional resonance points, and provides inspirational materials for the creation of cultural and creative products based on the user's emotional resonance path.

[0024] Compared with the prior art, this cultural and creative product VR virtual display method and system has the following beneficial effects:

[0025] 1. The present invention comprehensively collects relevant data of cultural and creative products and constructs an emotional database using an emotional context mining algorithm, thereby achieving accurate capture and in-depth analysis of the emotions of cultural and creative products. This not only improves the virtual display effect of cultural and creative products, but also enables users to deeply experience the emotional connotation of the products in VR scenes, thereby enhancing the users' emotional experience and resonance. Through the construction and application of the emotional database, the present invention provides a richer and more delicate means of emotional expression for the virtual display of cultural and creative products, making the displayed content more vivid and interesting.

[0026] 2. The present invention creates a highly immersive virtual display environment for users through a scene layout algorithm based on spatial emotion distribution, an emotion-driven action generation algorithm, an emotion dynamic music generation algorithm and a fusion emotion recognition algorithm. In this environment, users can not only interact deeply with cultural and creative products, but also obtain personalized feedback information based on their emotional resonance state, thereby further enhancing users' sense of participation and satisfaction.

[0027] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0029] Figure 1 This is a flow chart of a VR virtual display method for cultural and creative products;

[0030] Figure 2 This is a process operation diagram of a VR virtual display system for cultural and creative products. DETAILED DESCRIPTION

[0031] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0032] Embodiment 1

[0033] This embodiment describes a museum that wants to display a traditional embroidery cultural and creative product with a history of 100 years. The style of the embroidery has evolved in different historical periods and is closely linked to local cultural trends. The creator is a folk embroidery family with a wide social network. It is hoped that the audience will have a deep understanding of its cultural connotation and emotional value through VR display.

[0034] We comprehensively collected social and economic data from the time when the embroidery cultural and creative product was created, such as the level of development of the local handicraft industry and people’s income at that time. We also deeply mined cultural trend data, covering the impact of mainstream culture on embroidery patterns and color preferences, as well as unique embroidery style elements in regional cultural trends. We extracted emotional semantic labels such as “auspicious” and “dragon and phoenix” through cultural semantic analysis algorithms, obtained creators’ social network data, including family inheritance relationships and information on communication and interaction with peers, and collected detailed data on the evolution of embroidery in different historical periods, such as the change in design style from traditional flower and bird patterns to modern designs incorporating fashion elements, the change in usage scenarios from court use to popularization among the people, and the evolution of the audience group from aristocratic women to ordinary people. We used the evolution trend analysis algorithm to extract the trajectory of emotional evolution, and used the emotional context mining algorithm to build an emotional database. Where E db represents the comprehensive emotional index of the emotional database, n is the number of data categories, X i represents the i-th type of data, M i is the multi-dimensional feature mapping function for the i-th type of data, σ iis the weight parameter of the i-th category data, Y represents the creator's social network data, N is the sentiment propagation function of the social network data, and ρ is the weight of the creator's social network data, which provides data support for subsequent display.

[0035] Based on the emotion database, a hyper-realistic VR display scene is constructed, and a scene layout algorithm based on spatial emotion distribution is used. Among them, A j represents the area of ​​the jth emotional region, m is the number of emotional categories, E j represents the intensity value of the j-th emotion in the emotion database, ω j is the spatial influence weight of the jth emotion, S represents the total area of ​​the entire VR scene, and characters closely connected with cultural and creative products are set in each emotional area. The emotional expression actions of the characters are based on the emotion-driven action generation algorithm, which is: Among them A c represents the character's action amplitude and frequency parameters, p is the number of influencing factors, R l Indicates the role positioning information of the role, E r Indicates the sentiment value of the sentiment area, B l is the action generation function for the lth influencing factor, μ l The weight of the lth influencing factor is used to divide the scene into multiple emotional areas, such as the quiet and peaceful creation area and the lively and festive display area. According to the emotional characteristics of different areas, characters closely related to embroidery are set, such as the movements of embroidery artists concentrating on embroidery and the amazed expressions of customers when appreciating embroidery. The character movements are based on the emotion-driven action generation algorithm to make their movement amplitude and frequency conform to the emotional atmosphere of the scene. The weather effect simulation in the scene is dynamically adjusted according to the emotional rhythm information. For example, when displaying traditional festival themed embroidery, the weather effects are mainly sunny and breezy to enhance the festive atmosphere.

[0036] With the help of brain-computer interface technology, users can deeply interact with the characters in the VR scene. For example, when a user expresses his love for an embroidery pattern, the character responds according to a text generation algorithm based on emotional logic reasoning, telling the cultural story behind the pattern. Music rendering uses an emotional dynamic music generation algorithm. Among them, M g represents the musical note sequence, rhythm and harmony parameter set, r is the number of factors that affect the generation of music, I u Indicates the emotional intensity of the user's thinking intention feedback through the brain-computer interface, E s Indicates the emotional atmosphere intensity of the current VR scene, T m Represents the core emotional theme vector of cultural and creative products, C q is the music generating function for the qth influencing factor, ξ qis the weight of the qth influencing factor. Music is generated in real time according to the emotional characteristics of embroidery and the user's interactive emotional state. For example, when the user appreciates exquisite embroidery, the music is soothing and melodious to enhance the sense of immersion. When the user is interested in innovative embroidery design, the music rhythm is slightly faster to stimulate the user's desire to explore. The timbre of the instrument is dynamically switched according to the user's emotional experience trend, such as switching from the soft timbre of the guzheng to the bright timbre of the flute.

[0037] Multimodal biosensors are used to collect user physiological and behavioral data, and the degree of emotional resonance is determined by integrating emotion recognition algorithms. Where R em represents the quantitative value of emotional resonance, u is the number of combined types of physiological and behavioral data, and B t represents the physiological data collected by the t-th biosensor, V t represents the t-th behavior data, P t is the emotion mapping function for the t-th combination of physiological and behavioral data, λ t is the weight of the t-th combination of physiological and behavioral data, Z represents the overall interaction history data of the user in the VR scene, W is the emotional tendency function of the interaction history data, φ is the weight of the interaction history data, and when the user shows a strong resonance with the traditional cultural elements of embroidery and has a social tendency, the community matching algorithm recommends a virtual cultural and creative community to the user, where the user can share embroidery experiences and exchange cultural insights. At the same time, other cultural and creative products related to embroidery that fit their emotional resonance points are recommended to the user, such as accessories and household items with embroidery patterns as elements, and provide embroidery creation inspiration materials based on the user's emotional resonance path, such as innovative pattern design ideas and color matching skills.

[0038] Embodiment 2

[0039] This embodiment describes an art gallery preparing to display a modern sculpture cultural product created by a young artist. The sculpture is influenced by contemporary multicultural thoughts and integrates multiple artistic styles. The creator is active on social media and interacts frequently with many art lovers. The goal is to attract young audiences through VR display and stimulate their interest in modern art.

[0040] Collect socioeconomic data from the period when sculpture was born, such as the development of the contemporary art market and cultural consumption trends. Collect data on cultural trends, including the impact of popular culture and avant-garde art trends on sculpture creation concepts and forms of expression. Extract emotional semantic labels such as "innovation", "personality" and "rebellion". Obtain creators' social network data, analyze their works on social media and their interactions with fans, and sort out the evolution data of sculptures at different stages of creation, such as style adjustments from the initial concept to the shaping process, and changes in usage scenarios from personal creation to participation in public art projects. Use evolution trend analysis algorithms to clarify the trajectory of emotional evolution, and use emotional context mining algorithms to build an emotional database. Where E db represents the comprehensive emotional index of the emotional database, n is the number of data categories, X i represents the i-th type of data, M i is the multi-dimensional feature mapping function for the i-th type of data, σ i is the weight parameter of the i-th category data, Y represents the creator’s social network data, N is the sentiment propagation function of the social network data, and ρ is the weight of the creator’s social network data.

[0041] Based on the emotion database, a very modern VR display scene is constructed, and the emotional area is divided using the scene layout algorithm based on spatial emotion distribution. Among them, A j represents the area of ​​the jth emotional region, m is the number of emotional categories, E j represents the intensity value of the j-th emotion in the emotion database, ω j is the spatial influence weight of the jth emotion, S represents the total area of ​​the entire VR scene, and characters closely connected with cultural and creative products are set in each emotional area. The emotional expression actions of the characters are based on the emotion-driven action generation algorithm, which is: Among them A c represents the character's action amplitude and frequency parameters, p is the number of influencing factors, R l Indicates the role positioning information of the role, E r Indicates the sentiment value of the sentiment area, B l is the action generation function for the lth influencing factor, μ lThe weight of the lth influencing factor is given by the pixel value, which is the weight of the lth influencing factor. For example, the vibrant creative display area and the deep thinking art exploration area are used. Roles related to sculptures are set in each area. The role actions are generated based on the emotion-driven action generation algorithm, such as the passionate creation of artists in the creation area and the curious observation of audiences in the appreciation area. The weather effects in the scene are simulated according to the emotional rhythm. For example, when displaying sculptures with strong visual impact, the weather effects can be simulated as the depressing atmosphere on the eve of a storm to enhance the expressiveness of the sculptures. The rendering of special effect elements in the scene is dynamically triggered and the intensity is adjusted according to the emotional peak information. When the sculpture displays the climax of its unique artistic concept, the brightness and density of the special effect elements are greatly improved to attract the user's attention.

[0042] Users interact with VR scene characters through brain-computer interfaces. The character's response content uses a text generation algorithm based on emotional logic reasoning. For example, when a user asks about the inspiration for a sculpture, the character gives a detailed answer based on the artist's creative background and the scene's emotional logic. Music rendering is based on an emotional dynamic music generation algorithm. Among them, M g represents the musical note sequence, rhythm and harmony parameter set, r is the number of factors that affect the generation of music, I u Indicates the emotional intensity of the user's thinking intention feedback through the brain-computer interface, E s Indicates the emotional atmosphere intensity of the current VR scene, T m Represents the core emotional theme vector of cultural and creative products, C q is the music generating function for the qth influencing factor, ξ q is the weight of the qth influencing factor. Music is generated in real time according to the emotional characteristics of the sculpture and the user's interactive emotions. For example, when the user feels the innovation of the sculpture, the music has a strong rhythm and unique melody. As the user's emotional experience changes, the timbre of the instrument switches from electronic music elements to traditional instrument elements, creating a diverse artistic atmosphere.

[0043] Multimodal biosensors are used to collect user data, and a fusion emotion recognition algorithm is used to determine the degree of emotional resonance. Where R em represents the quantitative value of emotional resonance, u is the number of combined types of physiological and behavioral data, and B t represents the physiological data collected by the t-th biosensor, V t represents the t-th behavior data, P t is the emotion mapping function for the t-th combination of physiological and behavioral data, λ tis the weight of the tth combination of physiological and behavioral data, Z represents the user's overall interaction history data in the VR scene, W is the emotional tendency function of the interaction history data, φ is the weight of the interaction history data, if the user has a strong resonance with the innovative style of the sculpture and likes social sharing, the system recommends relevant virtual cultural and creative communities through the community matching algorithm, the user can meet like-minded art lovers in the community and exchange insights on modern art, and at the same time recommend other cultural and creative products with similar styles to the user, such as modern art paintings and creative home furnishings, and provide sculpture creation inspiration materials based on the user's emotional resonance path, such as new material application suggestions and cross-art form integration ideas.

[0044] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modifications to the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any brief modifications, changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A VR virtual display method for cultural and creative products, characterized in that: The specific steps of this method are: S1, data collection and analysis steps: Comprehensively collect data related to cultural and creative products, including social economic data, cultural trend data, creator social network data, and evolution data of cultural and creative products in different historical periods during the birth period of cultural and creative products, and use the emotional context mining algorithm to build an emotional database. The algorithm formula is: Where E db represents the comprehensive emotional index of the emotional database, n is the number of data categories, X i represents the i-th type of data, M i is the multi-dimensional feature mapping function for the i-th type of data, σ i is the weight parameter of the i-th category data, Y represents the creator’s social network data, N is the sentiment propagation function of the social network data, and ρ is the weight of the creator’s social network data; S2, VR scene construction steps: construct a hyper-realistic VR display scene based on the emotion database, and use the scene layout algorithm based on spatial emotion distribution to divide the scene into multiple emotion areas. The formula is: Among them, A j represents the area of ​​the jth emotional region, m is the number of emotional categories, E j represents the intensity value of the j-th emotion in the emotion database, ω j is the spatial influence weight of the jth emotion, S represents the total area of ​​the entire VR scene, and characters closely connected with cultural and creative products are set in each emotional area. The emotional expression actions of the characters are based on the emotion-driven action generation algorithm, which is: Among them A c represents the character's action amplitude and frequency parameters, p is the number of influencing factors, R l Indicates the role positioning information of the role, E r Indicates the sentiment value of the sentiment area, B l is the action generation function for the lth influencing factor, μ l is the weight of the lth influencing factor; S3, interaction and rendering steps: realize the deep interaction between users and characters in VR scenes, use brain-computer interface technology to capture users' thinking intention information, and interact with characters based on emotional resonance. Music rendering uses emotional dynamic music generation algorithm to generate music in real time according to the emotional characteristics of cultural and creative products and the interactive emotional state of users in VR scenes. The formula is: Among them, M g represents the musical note sequence, rhythm and harmony parameter set, r is the number of factors that affect the generation of music, I u Indicates the emotional intensity of the user's thinking intention feedback through the brain-computer interface, E s Indicates the emotional atmosphere intensity of the current VR scene, T m Represents the core emotional theme vector of cultural and creative products, C q is the music generating function for the qth influencing factor, ξ q is the weight of the qth influencing factor; S4, emotional resonance monitoring and feedback step: monitor the user's emotional resonance state, use multimodal biosensors to collect user physiological data and behavioral data, and judge the degree of emotional resonance by integrating the emotion recognition algorithm. The algorithm formula is: Where R em represents the quantitative value of emotional resonance, u is the number of combined types of physiological and behavioral data, and B t represents the physiological data collected by the tth biosensor, V t represents the t-th behavior data, P t is the emotion mapping function for the t-th combination of physiological and behavioral data, λ t is the weight of the tth combination of physiological and behavioral data, Z represents the user's overall interaction history data in the VR scene, W is the emotional tendency function of the interaction history data, φ is the weight of the interaction history data, and provides personalized feedback information based on the emotional resonance monitoring results, recommends cultural and creative products that are deeply in line with the user's emotional resonance points, and provides inspirational materials for the creation of cultural and creative products based on the user's emotional resonance path.

2. A VR virtual display method for cultural and creative products according to claim 1, characterized in that: In the data collection and analysis steps, the collection of cultural trends data not only covers mainstream cultural trends, but also deeply explores niche cultural schools and regional cultural trends information, and extracts unique emotional semantic labels through cultural semantic analysis algorithms. The algorithm formula is: Where L s represents the set of sentiment semantic labels, w is the number of cultural trend text fragments, K v represents the vth cultural trend text segment, D v is the semantic parsing function of the vth text segment, θ v is the weight coefficient of the vth text segment.

3. A VR virtual display method for cultural and creative products according to claim 1, characterized in that: In the VR scene construction step, when the scene is constructed, the weather effect simulation in the scene is dynamically adjusted according to the emotional rhythm information in the emotional database. For cultural and creative products that express passionate emotions and have a fast emotional rhythm, the weather effects are mainly violent storms, lightning and thunder. The weather change frequency formula is: where F w Indicates the frequency of weather changes, E p represents the emotional rhythm intensity value, α and β are adjustment coefficients, E j Focusing on the spatial emotional area division, E p Focus on the impact of emotional rhythm on weather effects.

4. A VR virtual display method for cultural and creative products according to claim 1, characterized in that: In the interaction and rendering step, in terms of the interaction between the user and the character through the brain-computer interface, the character's response content generation adopts a text generation algorithm based on emotional logic reasoning. The algorithm constructs the response text according to the user's thinking intention emotion, the scene emotional logic and the character's own emotional personality. The specific calculation method is: Where T r represents the semantic structure and vocabulary selection parameters of the response text, y is the number of influencing factors, I u Indicates the user’s thought intention and emotional information, S l Represents the scene emotional logic information, R p Indicates the character's emotional personality information, F x is the text generation function for the xth influencing factor, ∈ x is the weight coefficient of the xth influencing factor.

5. The method for VR virtual display of cultural and creative products according to claim 1, characterized in that: In the emotional resonance monitoring and feedback step, when using a multimodal biosensor to collect data, a filtering algorithm based on emotion feature optimization is used for data preprocessing. When the user is in a scene interaction with complex and changeable emotions, the algorithm performs targeted filtering on the collected data according to the emotion classification model in the emotion database. The filter parameter adjustment formula is: Among them G f represents the filtering parameters, E c It represents the emotional complexity value of the current scene, and γ and δ are adjustment coefficients.

6. A VR virtual display method for cultural and creative products according to claim 1, characterized in that: In the VR scene construction step, the rendering of special effect elements in the scene is dynamically triggered and the intensity is adjusted according to the emotion peak information in the emotion database. For cultural and creative products with strong emotional burst points, the brightness and density of special effect elements are greatly improved at the emotional peak moment. The special effect intensity adjustment formula is: Among them I e Indicates the strength of the special effect, E b represents the peak intensity value of emotion, and η and θ are conversion coefficients.

7. A VR virtual display method for cultural and creative products according to claim 1, characterized in that: In the interaction and rendering step, the instrument timbre of the music is dynamically switched according to the user's emotional experience trend in the VR scene during music rendering. When the user's emotional experience changes from calm to excited, the instrument timbre switches from soft string music to passionate brass music. The timbre switching threshold formula is: Where T s Indicates the tone switching threshold, E t represents the intensity of the user's emotional experience trend, and κ and λ are threshold adjustment coefficients.

8. The method for VR virtual display of cultural and creative products according to claim 1, characterized in that: In the emotional resonance monitoring and feedback step, in addition to providing personalized feedback information, a virtual cultural and creative community recommendation is also constructed based on the user's emotional resonance characteristics. If the user has a strong resonance with a certain emotional element and has a social tendency, the system recommends a virtual cultural and creative community to the user through a community matching algorithm based on the user's emotional resonance points, social behavior data, and the cultural atmosphere characteristics of the cultural and creative community. The algorithm formula is: Among them C m represents the recommendation list of virtual cultural and creative communities, a is the number of factors that affect community matching, and E z is the community matching function for the zth factor, R e m represents the quantitative value of the user's emotional resonance, U b Represents user social behavior data, C a Represents the cultural atmosphere feature vector of the cultural and creative community, ω z is the weight coefficient of the zth factor.

9. A VR virtual display method for cultural and creative products according to claim 1, characterized in that: In the data collection and analysis step, the evolution data of cultural and creative products in different historical periods are collected, including the collection of information on changes in design styles, usage scenarios, and audience groups in different eras, and the emotional evolution trajectory is extracted through the evolution trend analysis algorithm. The algorithm formula is: Where T ev represents the parameter set of emotion evolution trajectory, c is the number of evolution data categories, H b represents the b-th type of evolution data, G b is the trend analysis function of the b-th type of evolution data, τ b is the weight coefficient of the b-th type of evolution data.

10. A VR virtual display system for cultural and creative products, characterized in that: The system includes data collection and analysis module, VR scene construction module, interaction and rendering module, and emotional resonance monitoring and feedback module: The data collection and analysis module: comprehensively collects data related to cultural and creative products, including social economic data, cultural trend data, creator social network data, and evolution data of cultural and creative products in different historical periods during the birth period of cultural and creative products, and uses the emotional context mining algorithm to build an emotional database. The algorithm formula is: Where E db represents the comprehensive emotional index of the emotional database, n is the number of data categories, X i represents the i-th type of data, M i is the multi-dimensional feature mapping function for the i-th type of data, σ i is the weight parameter of the i-th category data, Y represents the creator’s social network data, N is the sentiment propagation function of the social network data, and ρ is the weight of the creator’s social network data; The VR scene construction module: constructs a hyper-realistic VR display scene based on the emotion database, and uses a scene layout algorithm based on spatial emotion distribution to divide the scene into multiple emotion areas. The formula is: Among them, A j represents the area of ​​the jth emotional region, m is the number of emotional categories, E j represents the intensity value of the j-th emotion in the emotion database, ω j is the spatial influence weight of the jth emotion, S represents the total area of ​​the entire VR scene, and characters closely connected with cultural and creative products are set in each emotional area. The emotional expression actions of the characters are based on the emotion-driven action generation algorithm, which is: Among them A c represents the character's action amplitude and frequency parameters, p is the number of influencing factors, R l Indicates the role positioning information of the role, E r Indicates the sentiment value of the sentiment area, B l is the action generation function for the lth influencing factor, μ l is the weight of the lth influencing factor; The interaction and rendering module: realizes the deep interaction between the user and the character in the VR scene, uses the brain-computer interface technology to capture the user's thinking intention information, and interacts with the character based on emotional resonance. The music rendering adopts the emotional dynamic music generation algorithm to generate music in real time according to the emotional characteristics of the cultural and creative products and the interactive emotional state of the user in the VR scene. The formula is: Among them, M g represents the musical note sequence, rhythm and harmony parameter set, r is the number of factors that affect the generation of music, I u Indicates the emotional intensity of the user's thinking intention feedback through the brain-computer interface, E s Indicates the emotional atmosphere intensity of the current VR scene, T m Represents the core emotional theme vector of cultural and creative products, C q is the music generating function for the qth influencing factor, ξ q is the weight of the qth influencing factor; The emotional resonance monitoring and feedback module: monitors the user's emotional resonance state, collects the user's physiological data and behavioral data using multimodal biosensors, and determines the degree of emotional resonance by integrating the emotion recognition algorithm. The algorithm formula is: Where R em represents the quantitative value of emotional resonance, u is the number of combined types of physiological and behavioral data, and B t represents the physiological data collected by the tth biosensor, V t represents the t-th behavior data, P t is the emotion mapping function for the t-th combination of physiological and behavioral data, λ t is the weight of the tth combination of physiological and behavioral data, Z represents the user's overall interaction history data in the VR scene, W is the emotional tendency function of the interaction history data, φ is the weight of the interaction history data, and provides personalized feedback information based on the emotional resonance monitoring results, recommends cultural and creative products that are deeply in line with the user's emotional resonance points, and provides inspirational materials for the creation of cultural and creative products based on the user's emotional resonance path.

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