# Visualization Practice and Communication Effect of Digital Chinese Films Based on Virtual Reality under Background of the Belt and Road Initiative

Authors: Dong Han; Jie Xu; Peng Chao
Journal: International Transactions on Electrical Energy Systems
 (2022)

---

## Abstract

Since the Belt and Road Initiative was proposed, it has received extensive attention from many aspects of the international community. To disseminate the ideas, development status, and construction achievements of the Belt and Road Initiative to the outside world has become a key and difficult problem in the development process of the initiative. Among different types of film and television, virtual reality technology should be the best interpretation of film communication. The film would bring a wider space for the development of the film by means of real reproduction and virtual reality and make the film’s record form more diversified. The continuous development and innovation of new media technology enable virtual reality to pass through panoramic lenses. As the most powerful technical support for the movie, it can even be converted into the user’s eyes to serve the movie so that the presentation of the movie has more new possibilities. In this context, the article aims to interpret the visualization practice and dissemination effects of digital Chinese films with virtual reality technology. The article used the mathematical expression of the visual SLAM problem to improve the process from the world coordinate system to the pixel coordinate system. The system is constructed, and the approximate calculation of the function is carried out. The constructed system was used in the experiments. This article conducts a survey of Google’s average popularity and a comparison of the voxelization process. The experimental data showed that the performance of Sponza in this branch of the sparse octree is 88.48 ms at the resolution of 100,000, which is weaker than 80.34 ms in the Dragon scene. The performance of the cascaded voxel texture is 6.889 ms, which is also weaker than Dragon’s 5.727 ms. The structure of the rules of the cascaded voxel texture scheme made it smoother to assist with the GPU, and the speed was the fastest in both the Dragon scene and the Sponza scene. The experimental content was well completed.


---

## Body

## 1. Introduction

The orientation and personalization of information dissemination is the development direction of the film. New media not only changed the mass communication characteristics of traditional media but also promoted the characteristics and focus of information communication. Of course, this change is inseparable from the development of digital technology. The development of digital technology has transformed the scarce channel resources of the original traditional media such as traditional TV and radio into abundant channel resources, such as big screen movies and online movies, which ensure that all types of viewers can choose a specific movie and give them more choices.In the visualization practice and dissemination effect of digital Chinese film, Wangbo believed that the advanced film education of arts and culture education aimed to narrow the cultural gap between generations by using digital equipment to produce works. It offered experiential communication, caring, and achievement opportunities through a project-based production process. His research aimed to examine the impact of storytelling and action learning pedagogies on high school film education achievement and trial and error. It constitutes the three phases of the high school film education curriculum. He believed that the future high school film education, as a kind of cultural and artistic education, would increase the interest of high school learners on the basis of this achievement. If systematic education is attempted, it would bring great development [1]. Huang believed that microfilms may be a new film world, which combines film art and network media. The rapid development of digital technology, network technology, and mobile communication technology has created various new media forms, brought about changes in communication methods, and laid a media technology foundation for the rise of microfilms. On the basis of the application of network media technology, the way of life of “network culture” and “microculture” constituted the foundation of microfilm social culture. Microfilms break through the limitations of the traditional film industry model, showing new features in terms of creation, production, dissemination, aesthetics, artistic time and space, and artistic expression [2]. Hebling brought performance experience that immerses participants in the possibilities of silent film. He described the basic setup of the device, as well as technical aspects related to network communication, motion capture, ultrasound, and visualization. In MovieScape, the audiovisuals generated in real time evoke recurring patterns of action from visitors. Audiovisual landscapes are selected via an imaginary steering wheel that is activated when the visitor clenches their fists. After this initial gesture, the sphere covered with the silent film image is modified by rotation and displacement, thereby changing the scene sequence, musical trajectory, and soundscape [3]. Mpp examined legislation related to minority languages on the one hand and cinema-related legislation on the other. He conducted a case study of films to analyze the challenges faced by small cinemas in the digital single market. His research was more about addressing the barriers to European film distribution—the problem of international distribution and the different practices of audiovisual translation—which have a big impact on films made in European minority languages. This means they were hard to compete with mass production. Although minority and regional languages are protected by EU legislation and diversity is a key factor in the EU narrative, the audiovisual policy does not directly address this protection [4]. With the development of the times, the share of digital films in their research began to decline, and the dissemination effect could not be well reflected.In this context, this paper uses virtual reality technology to study the visualization practice and dissemination effects of movies. In virtual reality, Kihonge described a comprehensive process for designing 4C space mechanisms in a virtual environment. Virtual reality allows users to view and interact with digital models in a more intuitive way than using a traditional human-machine interface (HCI) [5]. The central goal of the study by Freeman was to describe the potential of virtual reality for mental health, including consideration of the first two decades of application. There were early groundbreaking studies, but the methodological quality of the studies was generally low. There are wide gaps in meaningful mental health applications. The most recognized finding is that treatment based on virtual reality exposure reduces anxiety disorders, but there are many research and therapeutic avenues that are promising [6]. Fan studied the field of view prediction problem of viewers watching panoramic videos using commodity head-mounted displays (HMDs). Existing solutions either use the observer’s current orientation to approximate the future FOV or use historical orientation and dead reckoning algorithms to extrapolate the future FOV. His team developed a fixation prediction network that simultaneously leverages sensor and content-related features to predict future audience fixation. Sensor-related features include HMD orientation, while content-related features include image saliency maps and motion maps. Finally, he trained and validated two designs of the proposed network [7]. Dascal assessed the evidence supporting the use of virtual reality in acute inpatient medical settings. He used the PsycINFO, PubMed, and Medline databases to identify studies using the keywords virtual reality, virtual reality therapy, treatment, and hospitalized patients [8].Digitization is the technological foundation of information society, and digitization is sparking a broader media revolution. As a product of the digital age, virtual reality affects people’s production and lives at an unexpected speed. Technology is not only new technology for the development of the film industry but also a new vision, a new future, and a new platform to break the traditional film optical transmission mode. This paper would use virtual reality technology to make a system based on this technology to study the visualization practice and dissemination effect of digitized Chinese films.


## 2. Visualization Practice Method Based on Virtual Reality

### 2.1. Essence and Characteristics of Virtual Reality

Virtual reality (VR) technology is a virtual world created by humans and computers [9]. The simulation system tracks the dynamic and interactive behavior of users in real time through the real-time collection of multiple user data [10]. Among them, “virtual” refers to the nonexistent “virtual appearance” created by the computer through three-dimensional software and programming language [11]. “Reality” refers to the physical space that we can touch and see, or it can be the environment that is difficult to see and cannot exist in reality [12]. The traditional configuration software can meet the requirements of reflecting the factory implementation and collecting data. However, with the development of industry and more and more complex sites, the two-dimensional configuration interface can no longer meet the monitoring requirements of engineers for complex engineering environments.Virtual reality technology is a very cutting-edge and comprehensive discipline. It involves many professional fields such as computer science [13], human-computer interaction, graphic image art [14], and somatosensory technology [15]. It takes people as the center and collects the user’s behaviors and actions [16], position movement, and vision through somatosensory sensing technology, compiles them into data, and transmits them back to the database [17]. To achieve this effect, including text, speech, and other information superimposed into the real-world scene, it is necessary to integrate virtual information into the real-world scene in real time and output and display the final result. The database puts the user information collected in real time back into the virtual image, and the virtual image changes through the real-time user data [18]. This allows the virtual image to change with the user’s dynamic behavior. It achieves the effect of realistic restoration of reality [19]. Compared with the original control of “window” computer graphics through tools such as a mouse and keyboard, it is a step closer [20]. Human direct actions are involved in the interaction with the computer. Common enhanced display systems use hardware devices such as helmet-mounted displays and hand-held mobile processing devices. The quality of the operating platform would also affect the final fusion of the real world with 3D models and scenes. After the emergence of virtual reality technology, it has shown unlimited potential in tourism, real estate development and design, industrial design, new media art, and other directions. Feature point extraction and description, tracking, and registration technology are the most difficult points in AR systems. The current AR system classification in this paper is shown in Figure 1.Figure 1
Taxonomy of methods for implementing augmented reality.


### 2.2. Traditional System Structure of Augmented Reality

Handheld terminal augmented reality plays a huge role in many fields, such as car navigation, entertainment video, and advertising. Mobile augmented reality has reached unprecedented attention. The steps of the system are as follows: it first obtains the real-world scene through the camera and then detects the image of each frame in the video information separately. When there is a matching image, the tracking registration is performed. In the tracking registration system, the internal parameters of the camera should be calculated first. Then, we need to use the relationship between the feature point pairs to obtain the homography matrixH. After that, the rotation and translation matrices are calculated, and then, the virtual objects and real-life scenes are superimposed. It is necessary to save the feature information of some objects or pictures in the local database and then match the feature information extracted from each frame of the image in the video stream obtained by the camera with the feature information that has been saved in the local database, as shown in Figure 2:Figure 2
AR system implementation diagram.This change is not only the transformation of film and television shooting technology but also the aesthetics. Through the subtle changes in technology, it can profoundly affect all aspects of film production. Movies appear as an “entertainment medium.” When the movie legalizes the illegal plot because of the script, the audience’s perception and thinking follow the plot of the movie. In the research process of various disciplines, a knowledge base about the concept and the operation method of virtual reality technology itself has been established. There would be no sense of incongruity in the film that is unreasonable in reality. Compared with TV series, the movie clearly describes the story and moves the audience’s feelings in just two hours. This form of entertainment excels at moving people into their most relaxed state. The integration of AR thinking in the film can greatly enhance the interaction between the film and the audience, making the audience’s viewing experience a qualitative leap. The augmented reality system realized by computer vision mainly processes the collected video stream through image acquisition equipment.


### 2.3. Mathematical Formulation of Visual SLAM Problem

The visual SLAM problem can be described by two general basic mathematical equations, as shown in the following equations:(1)xk=fxk−1,uk,rk,(2)mk,n=hyn,xk,qk,n.The Gaussian difference function scale space is expressed as follows:(3)Hx,y,δ=Gx,y,kδ−Gx,y,δ∗Ix,y=Sx,y,kδ−Sx,y,kδ.The relationship between the two is as follows:(4)ϑGϑδ=δ∇2G.The measurement methods of the image plane, camera, and world plane coordinate system are all based on actual physical distance, while the measurement method of the image coordinate system is based on pixels. Therefore, a certain conversion of the unit scale is required. The conversion process is shown in Figure3.Figure 3
The process of the world coordinate system to the pixel coordinate system.From this, it can be known thatδ∇2G can be approximately expressed as follows:(5)δ∇2G=ϑGϑδ=Gx,y,kδ−Gx,y,δkδ−δ.We simplified to get the following equation:(6)Gx,y,kδ−Gx,y,δ=k−1δ2∇2G.We performed the Taylor expansion, which is as follows:(7)Hx=H+ϑHTϑXx+12xtϑ2Hϑx2x.Expanding equation (7) further, we can get(8)Hx^=H+12ϑHTϑXx^.The gradient amplitude can be expressed as follows:(9)mx,y=Sx+1,y−Sx−1,y2+Sx,y+1−Sx,y−12.The gradient direction can be expressed as follows:(10)θx,y=tan−1Sx,y+1−Sx,y−1Sx+1,y−Sx−1,y.We represented the Hessian matrix under the scale factor as follows:(11)Hx,δ=Lxxx,δLxyx,δLxyx,δLyyx,δ.The approximate calculation of the function is performed using the convolution calculated by the approximate filter, as shown in the following equation:(12)detHapp=CxxCyy−jCxy2,and using the gray-scale centroid method, the specific calculation is as follows: first, we define the moment of a certain image blockA:(13)meq=∑x,y∈Axp,yqIx,y.The direction vector of the feature point can be expressed as follows:(14)OZ⟶=arctanm01m10=arctan∑x,yyIx,y∑x,yxIx,y.We obtainedRθ, as shown in the following equation:(15)Rθ=cosθsinθ−sinθcosθ.


### 2.4. Visualizing Propagation Features

AR + VR mixed reality is also used in filmmaking. However, there is still a gap between VR movies and theoretical virtual reality technology. With the advancement of technology, there are more and more channels for audiences to obtain information. In an era full of massive information, people’s visual aesthetics are getting higher and higher, and the visual means with visual aesthetics also determine the dissemination effect of the film. Compared with traditional movies, VR movies have unique advantages in visual communication. Although traditional movie videos and pictures can objectively present the scene of the movie, they cannot use visual elements to interpret the nature of the movie like VR movies. The beautification of data visualization elements not only helps to attract the attention of the audience at the first time but also greatly improves the audience’s ability to recognize the movie. The charm of VR movies is to use visualization to display information intuitively to the audience. The beauty of visualization is not a simple superposition of colors and graphics. As far as the relationship between data intuition and aesthetics is concerned, the intuition of movie information should be first and the aesthetics of graphics should be second. Aesthetics are subject to intuition. In the future, the development of cloud computing, cloud storage, and the enrichment of VR content would stimulate the rapid development of the virtual reality industry. Although the production and development of virtual reality technology is not too short, it is basically used in research in professional and high-end academic fields, and only in recent years, it has developed into a new medium that can communicate with the public.The scientific use of color in VR movie visualization needs to be comprehensively considered from multiple perspectives such as hue, brightness, purity, and contrast. Using color stimulation to attract the audience’s attention and highlight the core connotation of the movie. At the same time, color is used to relieve the audience’s tension when watching VR movies and avoid visual fatigue of the audience. This technology is formed by the concentrated action of multiple technologies, and it is not a single technical level.


### 2.5. Virtual Panorama Technology

Because virtual reality technology first belongs to the category of computer science and technology, the research progress of early technology is related to computer science. A virtual reality panorama is a single projected image seamlessly stitched from a series of photos taken by a camera that rotates horizontally around the lens. Its origin is people’s pursuit of the authenticity of computer-generated scenes, so the idea of constructing virtual scenes based on photos is born. Photo-based virtual scenes are very realistic because they are photos, but they only reflect the environment of the scene from a certain angle, which is not perfect. It is also known as image-based imaging and is divided into cylindrical panoramas, spherical panoramas, and polygonal panoramas. The server virtualization architecture used by the system improved by this technology is shown in Figure4.Figure 4
Server virtualization architecture.


## 2.1. Essence and Characteristics of Virtual Reality

Virtual reality (VR) technology is a virtual world created by humans and computers [9]. The simulation system tracks the dynamic and interactive behavior of users in real time through the real-time collection of multiple user data [10]. Among them, “virtual” refers to the nonexistent “virtual appearance” created by the computer through three-dimensional software and programming language [11]. “Reality” refers to the physical space that we can touch and see, or it can be the environment that is difficult to see and cannot exist in reality [12]. The traditional configuration software can meet the requirements of reflecting the factory implementation and collecting data. However, with the development of industry and more and more complex sites, the two-dimensional configuration interface can no longer meet the monitoring requirements of engineers for complex engineering environments.Virtual reality technology is a very cutting-edge and comprehensive discipline. It involves many professional fields such as computer science [13], human-computer interaction, graphic image art [14], and somatosensory technology [15]. It takes people as the center and collects the user’s behaviors and actions [16], position movement, and vision through somatosensory sensing technology, compiles them into data, and transmits them back to the database [17]. To achieve this effect, including text, speech, and other information superimposed into the real-world scene, it is necessary to integrate virtual information into the real-world scene in real time and output and display the final result. The database puts the user information collected in real time back into the virtual image, and the virtual image changes through the real-time user data [18]. This allows the virtual image to change with the user’s dynamic behavior. It achieves the effect of realistic restoration of reality [19]. Compared with the original control of “window” computer graphics through tools such as a mouse and keyboard, it is a step closer [20]. Human direct actions are involved in the interaction with the computer. Common enhanced display systems use hardware devices such as helmet-mounted displays and hand-held mobile processing devices. The quality of the operating platform would also affect the final fusion of the real world with 3D models and scenes. After the emergence of virtual reality technology, it has shown unlimited potential in tourism, real estate development and design, industrial design, new media art, and other directions. Feature point extraction and description, tracking, and registration technology are the most difficult points in AR systems. The current AR system classification in this paper is shown in Figure 1.Figure 1
Taxonomy of methods for implementing augmented reality.


## 2.2. Traditional System Structure of Augmented Reality

Handheld terminal augmented reality plays a huge role in many fields, such as car navigation, entertainment video, and advertising. Mobile augmented reality has reached unprecedented attention. The steps of the system are as follows: it first obtains the real-world scene through the camera and then detects the image of each frame in the video information separately. When there is a matching image, the tracking registration is performed. In the tracking registration system, the internal parameters of the camera should be calculated first. Then, we need to use the relationship between the feature point pairs to obtain the homography matrixH. After that, the rotation and translation matrices are calculated, and then, the virtual objects and real-life scenes are superimposed. It is necessary to save the feature information of some objects or pictures in the local database and then match the feature information extracted from each frame of the image in the video stream obtained by the camera with the feature information that has been saved in the local database, as shown in Figure 2:Figure 2
AR system implementation diagram.This change is not only the transformation of film and television shooting technology but also the aesthetics. Through the subtle changes in technology, it can profoundly affect all aspects of film production. Movies appear as an “entertainment medium.” When the movie legalizes the illegal plot because of the script, the audience’s perception and thinking follow the plot of the movie. In the research process of various disciplines, a knowledge base about the concept and the operation method of virtual reality technology itself has been established. There would be no sense of incongruity in the film that is unreasonable in reality. Compared with TV series, the movie clearly describes the story and moves the audience’s feelings in just two hours. This form of entertainment excels at moving people into their most relaxed state. The integration of AR thinking in the film can greatly enhance the interaction between the film and the audience, making the audience’s viewing experience a qualitative leap. The augmented reality system realized by computer vision mainly processes the collected video stream through image acquisition equipment.


## 2.3. Mathematical Formulation of Visual SLAM Problem

The visual SLAM problem can be described by two general basic mathematical equations, as shown in the following equations:(1)xk=fxk−1,uk,rk,(2)mk,n=hyn,xk,qk,n.The Gaussian difference function scale space is expressed as follows:(3)Hx,y,δ=Gx,y,kδ−Gx,y,δ∗Ix,y=Sx,y,kδ−Sx,y,kδ.The relationship between the two is as follows:(4)ϑGϑδ=δ∇2G.The measurement methods of the image plane, camera, and world plane coordinate system are all based on actual physical distance, while the measurement method of the image coordinate system is based on pixels. Therefore, a certain conversion of the unit scale is required. The conversion process is shown in Figure3.Figure 3
The process of the world coordinate system to the pixel coordinate system.From this, it can be known thatδ∇2G can be approximately expressed as follows:(5)δ∇2G=ϑGϑδ=Gx,y,kδ−Gx,y,δkδ−δ.We simplified to get the following equation:(6)Gx,y,kδ−Gx,y,δ=k−1δ2∇2G.We performed the Taylor expansion, which is as follows:(7)Hx=H+ϑHTϑXx+12xtϑ2Hϑx2x.Expanding equation (7) further, we can get(8)Hx^=H+12ϑHTϑXx^.The gradient amplitude can be expressed as follows:(9)mx,y=Sx+1,y−Sx−1,y2+Sx,y+1−Sx,y−12.The gradient direction can be expressed as follows:(10)θx,y=tan−1Sx,y+1−Sx,y−1Sx+1,y−Sx−1,y.We represented the Hessian matrix under the scale factor as follows:(11)Hx,δ=Lxxx,δLxyx,δLxyx,δLyyx,δ.The approximate calculation of the function is performed using the convolution calculated by the approximate filter, as shown in the following equation:(12)detHapp=CxxCyy−jCxy2,and using the gray-scale centroid method, the specific calculation is as follows: first, we define the moment of a certain image blockA:(13)meq=∑x,y∈Axp,yqIx,y.The direction vector of the feature point can be expressed as follows:(14)OZ⟶=arctanm01m10=arctan∑x,yyIx,y∑x,yxIx,y.We obtainedRθ, as shown in the following equation:(15)Rθ=cosθsinθ−sinθcosθ.


## 2.4. Visualizing Propagation Features

AR + VR mixed reality is also used in filmmaking. However, there is still a gap between VR movies and theoretical virtual reality technology. With the advancement of technology, there are more and more channels for audiences to obtain information. In an era full of massive information, people’s visual aesthetics are getting higher and higher, and the visual means with visual aesthetics also determine the dissemination effect of the film. Compared with traditional movies, VR movies have unique advantages in visual communication. Although traditional movie videos and pictures can objectively present the scene of the movie, they cannot use visual elements to interpret the nature of the movie like VR movies. The beautification of data visualization elements not only helps to attract the attention of the audience at the first time but also greatly improves the audience’s ability to recognize the movie. The charm of VR movies is to use visualization to display information intuitively to the audience. The beauty of visualization is not a simple superposition of colors and graphics. As far as the relationship between data intuition and aesthetics is concerned, the intuition of movie information should be first and the aesthetics of graphics should be second. Aesthetics are subject to intuition. In the future, the development of cloud computing, cloud storage, and the enrichment of VR content would stimulate the rapid development of the virtual reality industry. Although the production and development of virtual reality technology is not too short, it is basically used in research in professional and high-end academic fields, and only in recent years, it has developed into a new medium that can communicate with the public.The scientific use of color in VR movie visualization needs to be comprehensively considered from multiple perspectives such as hue, brightness, purity, and contrast. Using color stimulation to attract the audience’s attention and highlight the core connotation of the movie. At the same time, color is used to relieve the audience’s tension when watching VR movies and avoid visual fatigue of the audience. This technology is formed by the concentrated action of multiple technologies, and it is not a single technical level.


## 2.5. Virtual Panorama Technology

Because virtual reality technology first belongs to the category of computer science and technology, the research progress of early technology is related to computer science. A virtual reality panorama is a single projected image seamlessly stitched from a series of photos taken by a camera that rotates horizontally around the lens. Its origin is people’s pursuit of the authenticity of computer-generated scenes, so the idea of constructing virtual scenes based on photos is born. Photo-based virtual scenes are very realistic because they are photos, but they only reflect the environment of the scene from a certain angle, which is not perfect. It is also known as image-based imaging and is divided into cylindrical panoramas, spherical panoramas, and polygonal panoramas. The server virtualization architecture used by the system improved by this technology is shown in Figure4.Figure 4
Server virtualization architecture.


## 3. Visualization Practice of Chinese Film and Experiment of the Communication Effect

### 3.1. Background Check

In recent years, compared with the previous experimental VR movies, VR technology has made breakthroughs. The addition of some interactive elements and sound positioning systems makes the VR experience more humanized. The Google Relative Interest Index survey results are shown in Figure5.Figure 5
Google average popularity.As shown in the figure, the interest index of Internet users in VR movies has shown a surge since 2015. As of November 2017, the interest index of Internet users in VR movies has remained at a high level.


### 3.2. Voxelization Process Comparison

In terms of the voxelization scale, this experiment counts the total amount of voxels in different scenes for the sparse octree and the concatenated voxel texture. Figure6 shows the scale comparison of Dragon and Sponza at 1283 resolution:Figure 6
Scale comparison of dragon and sponza at 1283 resolution.As shown in the figure, at a resolution of 1283, in the branch of the sparse octree, Dragon’s performance is 2.364, which is weaker than Sponza’s 3.135. In the Dragon scene, when the resolution is low, the voxel scales are about the same, and as the resolution increases, the gap between them also increases.In terms of voxelization speed, this experiment compares the time overhead of the sparse octree and cascaded texture voxelization schemes. It is also set at a resolution of 1283, as shown in Figure 7.Figure 7
Voxelization time comparison.As shown in the figure, at a resolution of 1283, the performance of Sponza in this branch of the sparse octree is 88.48 ms, which is weaker than 80.34 ms in the Dragon scene. The performance of the cascaded voxel texture is 6.889 ms, which is also weaker than Dragon’s 5.727 ms. The structure of the rules of the cascaded voxel texture scheme makes it smoother to assist with the GPU, and the speed is the fastest in both the Dragon scene and the Sponza scene.In terms of memory consumption, this experiment compares the memory consumption of the sparse octree and cascaded texture voxelization schemes. It is also set at a resolution of 1283, as shown in Figure 8.Figure 8
Comparison of memory consumption during voxelization.As shown in the figure, at a resolution of 1283, the performance of Sponza in the branch of the sparse octree is 6.06 MB, which is less than 10.56 MB in the Dragon scene. Both are the same in the cascaded voxel texture, which is 0.75 MB.


### 3.3. System and Satisfaction Evaluation

The system in this paper has been improved three times, each time the data matrix is expanded, and the amount of data is doubled. The specific hardware resource requirements of the system are shown in Table1.Table 1
Hardware resource requirements of the system.
Version 1Version 2Version 3CPU resource requirements20 GHz65 GHz96 GHzMemory resource requirements80 GB480 GB640 GBStorage space requirements10 TB30 TB40 TBAs can be seen from Table1, the third version of the system requires the highest hardware configuration. However, after a pairwise comparison, it can be found that the memory does not double after the data volume is doubled, which shows that the optimization of this version of the system is good enough.Through satisfaction evaluation, the satisfaction of VR visual experience in film communication is shown in Table2.Table 2
Satisfaction of VR visual experience in film communication.
ObjectVery dissatisfied (%)Not very satisfied (%)Uncertain (%)Satisfied (%)Very satisfied (%)AverageComprehensive information15.9218.3323.7125.6316.413.08Sensory experience12.8510.7217.0935.7623.583.48Clear picture18.8122.2628.7115.3514.872.85Immersion19.7418.6834.7914.7212.072.81Self-selection7.872.6223.1733.9132.433.82As can be seen from the table, the scores for autonomous selectivity and sensory experience are the highest, with 3.82 and 3.48 points, respectively. However, the picture clarity and immersion are only 2.85 points and 2.81 points, respectively. It shows that these two points still need to be strengthened.The statistics of the problems of VR visual experience in film communication are shown in Table3.Table 3
Statistics of problems in VR visual experience in film communication.
ObjectVery dissatisfiedNot very satisfiedUncertainSatisfiedVery satisfiedAverageFew themes3.8514.6225.7326.9228.883.62Messy picture7.1315.3120.1934.9422.433.49Poor interactivity2.172.5118.7634.4142.154.12Expensive VR5.427.5213.7320.1353.194.09Dizzy6.8414.5820.0736.3222.193.53As the table shows, audiences responded most strongly to poor interactivity and expensive VR equipment, scoring 4.12 and 4.09. Secondly, there are different degrees of dissatisfaction on issues such as vertigo and picture clutter, with scores of 3.53 and 3.49.Statistics on the audience’s favorite VR movie genres are shown in Table4.Table 4
Audience’s favorite types of VR movies.
ObjectCrime film (%)Martial arts film (%)War movie (%)Cartoon (%)Science fiction film (%)Comedy (%)Male92.0646.0369.8412.4634.9217.46Female7.4653.9730.7776.8266.0846.72As shown in the table, male and female audiences have different preferences for movie genres. For men, crime movies and war movies are more liked by 92.06% and 69.84%, respectively. For women, cartoons and science fiction films are more liked by 76.82% and 66.08%, respectively.


## 3.1. Background Check

In recent years, compared with the previous experimental VR movies, VR technology has made breakthroughs. The addition of some interactive elements and sound positioning systems makes the VR experience more humanized. The Google Relative Interest Index survey results are shown in Figure5.Figure 5
Google average popularity.As shown in the figure, the interest index of Internet users in VR movies has shown a surge since 2015. As of November 2017, the interest index of Internet users in VR movies has remained at a high level.


## 3.2. Voxelization Process Comparison

In terms of the voxelization scale, this experiment counts the total amount of voxels in different scenes for the sparse octree and the concatenated voxel texture. Figure6 shows the scale comparison of Dragon and Sponza at 1283 resolution:Figure 6
Scale comparison of dragon and sponza at 1283 resolution.As shown in the figure, at a resolution of 1283, in the branch of the sparse octree, Dragon’s performance is 2.364, which is weaker than Sponza’s 3.135. In the Dragon scene, when the resolution is low, the voxel scales are about the same, and as the resolution increases, the gap between them also increases.In terms of voxelization speed, this experiment compares the time overhead of the sparse octree and cascaded texture voxelization schemes. It is also set at a resolution of 1283, as shown in Figure 7.Figure 7
Voxelization time comparison.As shown in the figure, at a resolution of 1283, the performance of Sponza in this branch of the sparse octree is 88.48 ms, which is weaker than 80.34 ms in the Dragon scene. The performance of the cascaded voxel texture is 6.889 ms, which is also weaker than Dragon’s 5.727 ms. The structure of the rules of the cascaded voxel texture scheme makes it smoother to assist with the GPU, and the speed is the fastest in both the Dragon scene and the Sponza scene.In terms of memory consumption, this experiment compares the memory consumption of the sparse octree and cascaded texture voxelization schemes. It is also set at a resolution of 1283, as shown in Figure 8.Figure 8
Comparison of memory consumption during voxelization.As shown in the figure, at a resolution of 1283, the performance of Sponza in the branch of the sparse octree is 6.06 MB, which is less than 10.56 MB in the Dragon scene. Both are the same in the cascaded voxel texture, which is 0.75 MB.


## 3.3. System and Satisfaction Evaluation

The system in this paper has been improved three times, each time the data matrix is expanded, and the amount of data is doubled. The specific hardware resource requirements of the system are shown in Table1.Table 1
Hardware resource requirements of the system.
Version 1Version 2Version 3CPU resource requirements20 GHz65 GHz96 GHzMemory resource requirements80 GB480 GB640 GBStorage space requirements10 TB30 TB40 TBAs can be seen from Table1, the third version of the system requires the highest hardware configuration. However, after a pairwise comparison, it can be found that the memory does not double after the data volume is doubled, which shows that the optimization of this version of the system is good enough.Through satisfaction evaluation, the satisfaction of VR visual experience in film communication is shown in Table2.Table 2
Satisfaction of VR visual experience in film communication.
ObjectVery dissatisfied (%)Not very satisfied (%)Uncertain (%)Satisfied (%)Very satisfied (%)AverageComprehensive information15.9218.3323.7125.6316.413.08Sensory experience12.8510.7217.0935.7623.583.48Clear picture18.8122.2628.7115.3514.872.85Immersion19.7418.6834.7914.7212.072.81Self-selection7.872.6223.1733.9132.433.82As can be seen from the table, the scores for autonomous selectivity and sensory experience are the highest, with 3.82 and 3.48 points, respectively. However, the picture clarity and immersion are only 2.85 points and 2.81 points, respectively. It shows that these two points still need to be strengthened.The statistics of the problems of VR visual experience in film communication are shown in Table3.Table 3
Statistics of problems in VR visual experience in film communication.
ObjectVery dissatisfiedNot very satisfiedUncertainSatisfiedVery satisfiedAverageFew themes3.8514.6225.7326.9228.883.62Messy picture7.1315.3120.1934.9422.433.49Poor interactivity2.172.5118.7634.4142.154.12Expensive VR5.427.5213.7320.1353.194.09Dizzy6.8414.5820.0736.3222.193.53As the table shows, audiences responded most strongly to poor interactivity and expensive VR equipment, scoring 4.12 and 4.09. Secondly, there are different degrees of dissatisfaction on issues such as vertigo and picture clutter, with scores of 3.53 and 3.49.Statistics on the audience’s favorite VR movie genres are shown in Table4.Table 4
Audience’s favorite types of VR movies.
ObjectCrime film (%)Martial arts film (%)War movie (%)Cartoon (%)Science fiction film (%)Comedy (%)Male92.0646.0369.8412.4634.9217.46Female7.4653.9730.7776.8266.0846.72As shown in the table, male and female audiences have different preferences for movie genres. For men, crime movies and war movies are more liked by 92.06% and 69.84%, respectively. For women, cartoons and science fiction films are more liked by 76.82% and 66.08%, respectively.


## 4. Virtual Reality Technology and Visual Perception

### 4.1. Overview of Visual SLAM

In the general case of light pulses, the quality of the image data obtained by the sensor directly affects the localization and estimation of the forward optical odometer. If the information noise of the acquired image data exceeds a certain range due to the sensor itself, the discrepancy between the local map constructed from the optical kilometers and the actual scene would increase, which may eventually lead to the inability to estimate the position. Second, the actual timing and precision of the image data obtained from the sensor also affect the relative working of the optical odometer. For practical requirements, the normal operation of the sensor should not be limited by the characteristics of a specific environment or object, except for some of its characteristics. Finally, the initial values obtained from optical kilometers directly determine the usability of the results of the entire optical strike system. In the actual implementation process, we can use the advantages of the sensor to improve the working efficiency of the optical pathfinder and make the entire optical framework smoothly.


### 4.2. Use of Sound-Focused Language in All Dimensions

In the case that the lens language is relatively weakened, the virtual reality film enhances the effect of the sound language on the film as a whole, which can interact and complement each other. Such films require the help of virtual reality equipment to allow the audience to enter the environment of the story. It is by virtue of this, compared with traditional film and television works, through the use of sound language in virtual reality films, one can bring one’s own emotions into the story of the film at a deeper level.Among the human five senses, the ear is one of the most sensitive organs. In real life, there are many types of music mobile software that would especially open a music playlist or radio station called “3D Surround Sound.” The songs in the software are processed through digital interactive 3D positioning sound technology. They process the original 2D, relatively flat sound into a three-dimensional effect so that when listening to music, it produces a real feeling of listening to a live concert. The sound language presented in virtual reality movies and the listening experience presented by 3D surround sound are similar. The expressive power of sound and language is no less than the impact of pictures. It is precisely because of the weakening of the role of virtual reality films in the language of the lens that the sound elements in the audio-visual language also make a contribution to the embodiment of immersion.Image data acquisition: in visual SLAM, it generally refers to reading the information of multiple pictures or picture streams acquired by the camera and the preprocessing process. Visual odometry, also known as visual front end, is responsible for providing estimates of camera motion and optimized initial values such as local map models for back-end nonlinear optimization. Loopback detection, also known as closed-loop detection, is responsible for detecting and judging the historical position information and real-time position information of the robot. If the location information is the same, it is submitted to the back-end nonlinear optimization for processing.


### 4.3. Technical Exploration of Visual Effects

To explore the technical level of visual effects, we can start from the branch of their details. The capture of real photography in the early stage, the false creation of real-shot images in the later stage, and how to combine the two effectively and harmoniously are the necessary steps for visual effects to achieve excellent results. Before the advent of the digital age, VFX had its corresponding technical skills, such as frame-by-frame animation, miniature models, motion masks, and scenography. In the field of visual effects, corresponding changes have been made to traditional techniques, including motion control systems, motion capture systems, computer animation, computer modeling, and computer synthesis. At the same time, different kinds of digital tools have been derived, such as Houdini, which is good at computer post-processing, and Maya, which is good at animation and computer modeling. If the noise of the acquired image data information exceeds a certain range due to the sensor itself, then the local map constructed by the visual odometry would inevitably deviate from the real scene, which may eventually lead to the failure of positioning estimation.Although the visual effects present false images, their purpose is to expound the essence of the film’s story so as to attract the viewer’s attention. To the extent that a pure virtual image wants to hit the audience’s mind, it also needs to have an important attribute, that is, visual realism. The hallmark of this style is that it creates a level of realism in paintings that is almost identical to photography. The so-called visual realism is to make viewers themselves unable to distinguish the authenticity of the pictures presented in the film. Although viewers are aware of the fictional characteristics of the scenes when they see the grand or wonderful phantom scenes, the real texture of the pictures and people’s cognition reach a consensus. It would not deepen the audience’s suspicion of the film’s story but can make the meaning and emotion expressed by the film’s story more real and thorough to the audience.However, VR movies also face challenges. The main problem with VR movies is that they rely too much on the initial visual impact brought by VR technology while ignoring the narrative quality that a movie should have. When the audience’s initial curiosity about VR disappears, VR movies still face the requirements of content quality. The industry should return to the central essence of the traditional film business model, that is, telling the story that is supposed to be told and delivering the live action to the widest possible audience using the most comprehensive, effective, and broadest medium. At present, many producers have produced a batch of low-quality VR works without a good grasp of this technology. These works not only eliminate the original media potential of VR technology but also greatly reduce the communication influence of these producers.


## 4.1. Overview of Visual SLAM

In the general case of light pulses, the quality of the image data obtained by the sensor directly affects the localization and estimation of the forward optical odometer. If the information noise of the acquired image data exceeds a certain range due to the sensor itself, the discrepancy between the local map constructed from the optical kilometers and the actual scene would increase, which may eventually lead to the inability to estimate the position. Second, the actual timing and precision of the image data obtained from the sensor also affect the relative working of the optical odometer. For practical requirements, the normal operation of the sensor should not be limited by the characteristics of a specific environment or object, except for some of its characteristics. Finally, the initial values obtained from optical kilometers directly determine the usability of the results of the entire optical strike system. In the actual implementation process, we can use the advantages of the sensor to improve the working efficiency of the optical pathfinder and make the entire optical framework smoothly.


## 4.2. Use of Sound-Focused Language in All Dimensions

In the case that the lens language is relatively weakened, the virtual reality film enhances the effect of the sound language on the film as a whole, which can interact and complement each other. Such films require the help of virtual reality equipment to allow the audience to enter the environment of the story. It is by virtue of this, compared with traditional film and television works, through the use of sound language in virtual reality films, one can bring one’s own emotions into the story of the film at a deeper level.Among the human five senses, the ear is one of the most sensitive organs. In real life, there are many types of music mobile software that would especially open a music playlist or radio station called “3D Surround Sound.” The songs in the software are processed through digital interactive 3D positioning sound technology. They process the original 2D, relatively flat sound into a three-dimensional effect so that when listening to music, it produces a real feeling of listening to a live concert. The sound language presented in virtual reality movies and the listening experience presented by 3D surround sound are similar. The expressive power of sound and language is no less than the impact of pictures. It is precisely because of the weakening of the role of virtual reality films in the language of the lens that the sound elements in the audio-visual language also make a contribution to the embodiment of immersion.Image data acquisition: in visual SLAM, it generally refers to reading the information of multiple pictures or picture streams acquired by the camera and the preprocessing process. Visual odometry, also known as visual front end, is responsible for providing estimates of camera motion and optimized initial values such as local map models for back-end nonlinear optimization. Loopback detection, also known as closed-loop detection, is responsible for detecting and judging the historical position information and real-time position information of the robot. If the location information is the same, it is submitted to the back-end nonlinear optimization for processing.


## 4.3. Technical Exploration of Visual Effects

To explore the technical level of visual effects, we can start from the branch of their details. The capture of real photography in the early stage, the false creation of real-shot images in the later stage, and how to combine the two effectively and harmoniously are the necessary steps for visual effects to achieve excellent results. Before the advent of the digital age, VFX had its corresponding technical skills, such as frame-by-frame animation, miniature models, motion masks, and scenography. In the field of visual effects, corresponding changes have been made to traditional techniques, including motion control systems, motion capture systems, computer animation, computer modeling, and computer synthesis. At the same time, different kinds of digital tools have been derived, such as Houdini, which is good at computer post-processing, and Maya, which is good at animation and computer modeling. If the noise of the acquired image data information exceeds a certain range due to the sensor itself, then the local map constructed by the visual odometry would inevitably deviate from the real scene, which may eventually lead to the failure of positioning estimation.Although the visual effects present false images, their purpose is to expound the essence of the film’s story so as to attract the viewer’s attention. To the extent that a pure virtual image wants to hit the audience’s mind, it also needs to have an important attribute, that is, visual realism. The hallmark of this style is that it creates a level of realism in paintings that is almost identical to photography. The so-called visual realism is to make viewers themselves unable to distinguish the authenticity of the pictures presented in the film. Although viewers are aware of the fictional characteristics of the scenes when they see the grand or wonderful phantom scenes, the real texture of the pictures and people’s cognition reach a consensus. It would not deepen the audience’s suspicion of the film’s story but can make the meaning and emotion expressed by the film’s story more real and thorough to the audience.However, VR movies also face challenges. The main problem with VR movies is that they rely too much on the initial visual impact brought by VR technology while ignoring the narrative quality that a movie should have. When the audience’s initial curiosity about VR disappears, VR movies still face the requirements of content quality. The industry should return to the central essence of the traditional film business model, that is, telling the story that is supposed to be told and delivering the live action to the widest possible audience using the most comprehensive, effective, and broadest medium. At present, many producers have produced a batch of low-quality VR works without a good grasp of this technology. These works not only eliminate the original media potential of VR technology but also greatly reduce the communication influence of these producers.


## 5. Conclusion

With the vigorous development of the Internet and cloud computing, the amount of data generated by human use of the network has grown exponentially. Under the current situation of such data explosion, virtual reality technology came into being. This paper adopts virtual reality technology to study the visualization practice and dissemination effect of digitized Chinese films. This paper explores the essence and characteristics of virtual reality and categorizes the methods for realizing augmented reality. Then, the traditional system structure of augmented reality is constructed, and the AR system implementation diagram is drawn. The research on the characteristics of visual propagation is carried out, the virtual panorama technology is enriched, and the server virtualization architecture is constructed. In the experiment, this paper improves the system three times, each time the data matrix is expanded, and the amount of data is doubled. A satisfaction survey was conducted to investigate the satisfaction of VR visual experience in film communication, the statistics of VR visual experience in film communication, and the audience’s favorite type of VR film. Finally, it explores the technology that emphasizes the use of sound language and visual effects in all dimensions. The experimental data of the article show that audiences respond most strongly to poor interactivity and expensive VR equipment, with scores of 4.12 and 4.09. Secondly, there are different degrees of dissatisfaction on issues such as vertigo and picture clutter, with scores of 3.53 and 3.49. In the follow-up research study, the efficiency of the system can be further improved, and the delivery of the communication effect can be linked with big data.



---

*Source: 4850488-2022-09-16.xml*