An Empirical Study on the Protection and Intelligent Inheritance Strategies of Folk Dance Art in the Digital Environment

As an important part of the culture of each ethnic group, folk dance carries a deep historical heritage and unique cultural connotation, and shows a rich variety of regional characteristics [1–2]. Ethnic folk dance in different regions shows obvious differences in dance steps, dance posture, costumes and other aspects, reflecting the local people’s living customs, religious beliefs, natural environment and other factors. In the expression of ethnic folk dance, people can often feel the life attitude, emotional expression and spiritual pursuit of the people of the ethnic group, and some dance works show the people of the ethnic group’s reverence and worship of nature, reflecting the people’s love of life and the hope for the future [3–5].

Ethnic folk dance is an important embodiment of national cohesion and identity, and assumes an important role in the process of national unity and development, not only as a carrier of national cultural heritage and development, but also as a symbol of national identity and cohesion [6–7]. Through joint participation in ethnic folk dance activities, it can enhance the emotional exchange of people of all ethnic groups, strengthen the unity of all ethnic groups, and promote the prosperity of all ethnic cultures [8–9]. Ethnic folk dance has rich local color, unique emotional transmission and strong cohesion of national unity, tells the unique stories and spirituality of different ethnic groups, and has irreplaceable significance for the inheritance and development of national culture [10–12].

Information digitization technology is a new technology with the development of the times and scientific and technological progress, this technology is not only capable of storing information such as graphics, video, sound, etc., but also capable of creating virtual objects, visualization things, etc., which greatly facilitates the protection and inheritance of folk dances. The rational use of digital equipment provides great convenience for the protection and inheritance of folk dance [13–14]. For example, the video camera is able to film the dance performances for repeated playback, the scanner can completely copy the picture information and save it to the computer for viewing and printing at any time, and the Internet database can store the information of large-volume materials and be able to output them in reverse regardless of the limitations of time and space. The integration of these new technologies further promotes the progress of folk dance conservation [15–17].

This study analyzes digital technology for the preservation and inheritance of folk dance art and investigates the effects of its application in dance art. The accuracy of digital technology in dance motion capture is evaluated by utilizing motion capture data acquisition methods in dance movements, including human body detection, extraction, and posture estimation. On this basis, a platform for digitalization protection and inheritance of folk dance art is developed, and the practical application effect of this paper’s platform in the protection and inheritance of the art is evaluated through the assessment of the platform’s usability as well as the dissemination effect of folk dance art.

2

Application of digital technology in the preservation of folk dance art

Digitization is the conversion of complex analog data into digital signals or digital codes for transmission and processing through computers. Mature digital technology is the basis and guarantee for safeguarding intangible cultural heritage digitally. Digital preservation refers to the use of digital technologies such as digital acquisition, storage, processing, display, and dissemination to transform, reproduce, and restore cultural heritage into shareable and renewable digital forms.

2.1

Accurate real-time rendering

Fast rendering is an important application in digital technology. In order to better express the realism of the virtual scene, a common method is to use polygonal grids to model it. The essence of real-time rendering technology is to calculate and print the image in real time, while also drawing and displaying the image in a shorter time. In addition, because it is difficult for a single rendering system to render massive data in real-time, a distributed rendering system can be used to achieve real-time parallel rendering of 3D scenes.

2.2

Virtual presentation

VR (Virtual Reality), which is frequently utilized for digital presentations of cultural heritage, encompasses desktop VR technology, headset VR technology, and projected VR technology. Desktop VR is based on a desktop computing environment where users interact with a virtual reality system. Head-mounted VR presents a virtual scene with the help of a VR headset display, where the user’s vision is completely replaced by the content of the headset, making it highly immersive. However, because it blocks the exchange of information between the user and the real world, communication between people becomes more difficult Projection VR, which utilizes a projection system to achieve a virtual display, has a very wide field of view and is widely used in the virtual display of large sites.

2.3

Multidirectional human-computer interaction

Human-computer interaction technology is essential in the implementation and optimization of the virtual experience system for folk dance art heritage. Due to multiple limitations such as computing and storage, the heritage preservation system in virtual reality encounters many problems with realtime and interactivity. One of the most natural, direct, and real interaction modes is when the user is in the physical space, and the virtual environment is driven to change by their own movement. In this type of virtual reality system, localization is a very important task.

2.4

Research and Analysis on the Recognition of Digital Technology in Folk Dance

The rapid development of digital technology has enabled the use of digital technology to preserve folk dance art in a digital format, which can restore its artistic original appearance to the greatest extent.

This section analyzes the impact of digital technology on folk dance art through a questionnaire survey. On the four dimensions of “artistic protection”, “artistic propagation”, “artistic inheritance” and “artistic innovation”, we analyze the effect of digital technology in folk dance art. The questionnaire was designed in four dimensions. Each dimension contains 5 survey items, and 200 folk dance artists were selected to assess the recognition of digital technology application in dance art. The ratings were divided into “very disapproving”, “disapproving”, “average” and “approving”, The mean scores of the different dimensions of the survey were calculated and tallied.

The results of the survey on the recognition of digital technology based on different dimensions are shown in Figure 1. The data in the figure show that folk dance artists have a high degree of recognition of the above four dimensions, and the order of the degree of recognition is as follows: “the role of artistic inheritance” (4.70), “the role of artistic protection” (4.44), “the role of artistic innovation role” (4.39), and “art innovation role” (4.16). It is worth mentioning that the ratings of digitization technology in the dimensions of “role of art inheritance” and “role of art protection” are relatively high. Digital presentation through digital technologies such as two-dimensional planar presentation, three-dimensional simulation spatial presentation, digital interactive presentation, establishment of folk dance art database, computer-assisted restoration of folk dance art, etc., has promoted the protection and inheritance of folk dance art.

3

Motion Capture Data Acquisition in the Digitization of the Dance Arts

3.1

Body Detection and Extraction

3.1.1

Shape-based human detection

The shape and motion of human body is very different from that of other objects in the scene, therefore, based on the a priori knowledge such as human body shape, human body detection is tracked in a complex background, and then the human body contour is extracted using relevant foreground extraction methods. In recent years, many shape descriptions have been successfully applied in human body detection, such as Haar wavelet features [18], edge features, and histogram of gradient direction features (HoG) [19–20].

For the image to be detected, HoG operators are extracted and then trained and localized using SVM to output the location of the human body. However, the HoG human body detection algorithm is a single-model and can only detect frontal and back human bodies, while it is not effective for side human bodies. By extending the HoG algorithm, the variable part model (DPM) is proposed, a model that divides the detection target into several sub-targets to be trained separately, and finally finds a model with the optimal degree of matching.

3.1.2

Human motion detection and extraction

Motion-based human detection and extraction methods rely on the difference between the current frame and the previous image frame for localization and foreground extraction. The main methods are background subtraction, frame difference, and optical flow.

The basic idea of the background subtraction method is to use the difference between the current frame image and the background image to detect the motion region, which is suitable for image sequences with a fixed background. Taking the simplest background subtraction algorithm as an example, if I_b (x), I_c (x) is the gray value of the current background image I_b and the current frame image I_c at pixel x respectively, and T is the threshold threshold: 1 ${\begin{array}{l} x \in Prospects & if | I_{c} (x) - I_{b} (x) | > T \\ x \in Background & other \end{array}$

3.1.3

Multi-view geometric foreground extraction

In multi-view images, the geometric relationship between multiple views is also important information, and considering the spatial consistency between multi-view images, guiding each single image for target contour extraction has also received the attention and research of many scholars.

For a 2D object S with a smooth surface and a set of multi-view image projections R ={r_i : i = 1…n}, VH(S.R) is a visual convex packet reconstructed from the n =|R| multi-view images, i.e., a polygon consisting of 2n edges. Let R_i = R – {r_i}, then: 2 $S \leq V H (S . R) \leq V H (S . R .) . \forall i .$

Also meet: 3 $S i l_{i} = P_{i} (S) \leq P_{i} (V H (S, R,))$ where Sil_i is the outline of the i th viewpoint and P_i(*) is the projection transformation of the object S or VH in the i th viewpoint. The above constraints are extended to three-dimensional space, and the constraints remain: 4 $S i l_{i} \leq P_{i} (V H (S, R_{i})) . \forall i .$

3.2

Human Body Posture Estimation

3.2.1

Human Skeleton and Shape Representation

Depending on the requirements of the motion capture [21] system, human body models representing different levels of detail can be used to participate in pose estimation. At the same time, different methods have different requirements for the human body model, and the computational complexity varies greatly. However, they can usually be categorised into stick models, body models, and 3D surface models. 1)

Stick model: According to the definition of the tree structure of the human skeleton, the human skeleton is represented by simple line segments linking neighboring joints. The stick model is the simplest, intuitive, and less computationally intensive model of the human skeleton.

2)

Body model: Each limb of the human body is viewed as a rigid body, and the shape of each limb of the human body is approximated using parametrically described three-dimensional geometries, such as ellipsoids, cylinders, or circular platforms, etc. The human body’s motion is the result of the movement of each limb of the human body. The motion of the human body is driven by the skeleton for rigid body motion, mainly rotational and translational motion.

3)

3D surface model: the 3D surface model is a two-layer structure, with the human skeleton represented by a stick model in the inner layer and the skin represented by a large number of triangular meshes in the outer layer. In estimating human posture, the stick model drives the deformation of human skin, which encompasses both rigid body motion and non-rigid body deformation. A 3D surface model is utilized to create a more realistic depiction of human motion and skin deformation.

3.2.2

Human visual characteristics

1)

Human contour

The human body contour is defined as the projection of the real human body in the image plane, which can give information about the position of the human body in space, while the contour still maintains a large amount of information reflecting the human body’s posture and behavior. From the perspective of the human geometric model, the contour features of the human body model can be directly obtained by projecting the entire 3D model onto the corresponding camera plane. Meanwhile, since the vertices of the a priori human body model have been bound to the corresponding human skeleton, the contours of the human body model can also provide richer information about the human body’s pose than the contours extracted from the image.

2)

Edge characterization

An edge is where an image’s gray scale or color changes abruptly and is not affected by ambient light. The simplest and most commonly used edge extraction operators are the Laplacian and Canny operators.

The goal of the Canny operator is to find an optimal edge detection algorithm, which means that the algorithm is able to identify as many actual edges in the image as possible. The edges that have been identified must be as close as possible to the actual edges in the actual image.

3.3

Calculation of dance motion capture accuracy based on digital technology

This experiment was conducted on a PC with a Core(TM) i5-3470 3.2GHz CPU and 4GB RAM, using Matlab as the development environment. The dance movement database created contains 20 sets of folk dance movement clips with about 1000 frames each. This paper focuses on the final movement of the left arm in a single dance movement (within 0-20s) for experimental comparison. The experimental subject is a folk dance artist, and the left arm joint point movement characteristics of the experimental subject are extracted by digital technology and compared with the standard movement, so as to evaluate the accuracy of digital technology in the dance movement capture, and the accuracy calculation formula is as follows: 5 $A = 1 - \frac{| Test value - Standard value |}{Standard value}$

The main movements of the subject and the standardized movements are contrasted in Figure 2. As a result of the comparative analysis of the differences, the differences between the standard movements of “left arm swing direction”, “left arm joint angle movement” and “left arm and torso angle” captured by the digital technology are relatively small. The average accuracy of each motion capture is 0.988, 0.986, and 0.984 respectively.

Through the comparison of the experimental results, it is verified that the similarity matching method of digital technology can clearly and efficiently detect the differences and standards between the movement objects, with high robustness, which lays a foundation for the digital protection and inheritance of folk dances.

4

Design of a platform for the digital preservation and transmission of folk dances

4.1

User experience design

User experience design, a user-centered design tool, is designed with the user’s needs in mind. The design process focuses on user-centeredness, and the concept of user experience is included from the earliest stage of development and runs through the entire process. User experience is the feeling established during the process of using a product or enjoying a service.

User experience is critical to all products and services, and is especially important in the design of digital platforms. According to The Elements of User Experience, the UX process consists of the following five dimensions: 1)

Strategy layer: i.e. the purpose of the digital platform design.

2)

Scope layer: i.e. the analysis of user needs and the best way to realize functions.

3)

Structure layer: this layer focuses on how to convey information to users, and is expressed in the form of a flowchart in digital platform design.

4)

Framework layer: it determines the functions and forms realized by the platform, and its expression is the interaction prototype diagram.

5)

Expression layer: it is the perception design, which satisfies the sensory feelings of users, and in simple terms, it is the interface design of the platform system.

4.2

Platform design objectives

The protection of intangible cultural heritage is not to protect a certain heritage, a certain vessel or a certain building, but the core of it is to protect the spiritual product, which is the intangible knowledge level protection. Therefore, the objective of the design of the digital protection platform for folk dance intangible cultural heritage should be in line with the knowledge expression model, and completely express the cultural and intellectual attributes of folk dance art. The model of folk dance knowledge expression and dissemination is depicted in Figure 3. 1)

Folk dance knowledge source layer. It contains different cultural knowledge sources, mainly including picture resources such as dance works and dance elements, text resources such as historical documents, information about dance artists and techniques, as well as video resources such as interviews with dance artists and the production process of dance works.

2)

The folk dance knowledge description layer is based on the knowledge source layer, exploring the constituent elements of folk dance culture from multiple perspectives according to the attributes and characteristics of folk dance culture, such as systematicity, complexity, and internal concealment, etc., extracting the knowledge characteristics of the dance culture, and categorizing and archiving the collected knowledge sources.

3)

The folk dance Expression and Application Layer is a knowledge layer that makes full use of the knowledge sources and displays folk dance culture in an all-round way on the basis of the Knowledge Source Layer and the Knowledge Description Layer.

4.3

Platform system architecture

The system architecture of the digital protection and inheritance platform of folk dance art is shown in Figure 4.

4.3.1

Artistic conservation database system

The folk dance Database System is the knowledge source layer of the entire digital preservation platform, and other dissemination and application systems must rely on interactions with the database system in order to realize the functions of their respective systems. The database system contains three sub-databases: 1)

Multimedia database of traditional folk dance culture

Through 2D scanning, image shooting, video capturing, text input and other digitizing techniques, the collected folk dance cultural resources are stored in this database.

2)

Folk Dance Comprehensive Application Dance Material Database

The preservation of folk dances should fully express the characteristics of living heritage and the continuity of time. This dance material database is mainly intended to inform about the material resources that assist in the development of modern dance.

3)

Folk Dance Innovation Sharing Database

Include those that utilize the platform’s innovative design application system to design outstanding dance works, or dance artists who share their dance techniques and dance cultural connotations.

4.3.2

Multi-layer categorized search and sharing system

The multi-level categorized search and sharing system relies on resource management and service technology, which is mainly divided into two modules: front office service and back office management. The backstage camping management is mainly responsible for two parts. The first is the updating and repairing of the existing resources in the database and the synchronous management of the organizational structure. The second task is to review content, enter data, and manage permissions for network resources. Network resources can include new dance works produced by dance artists, video interviews of dance artists, and other digital resources that are part of the multimedia database of traditional folk dance culture. The front end service part mainly responds to user access requests with different permissions and provides various services based on the folk dance database. It mainly contains: 1)

Multi-level semantic search of the resource catalog of the folk dance database system.

2)

Resource permission sharing service

4.3.3

Multimedia Dissemination Application System

Making full use of a variety of information technologies such as 3D animation technology, virtual reality technology, semantic Web technology, knowledge visualization technology, the multimedia communication application system mainly contains three subsystems: 1)

Multimedia Interactive Display Subsystem for Folk Dance

Through the folk dance multimedia interactive display subsystem, text, image, video and sound are combined together to receive information through human multidimensional senses in a richer and more graphic way, which helps to understand and receive the dance cultural information, stimulate the public’s interest in folk dance and leave a deep impression, improve the knowledge absorption rate, and combine with the simple interactive behaviors, so that the culture can be spread and develop in a more natural communication environment.

2)

Folk Dance Innovation Design Creation Experience Subsystem

The innovative design creation experience sub-system is created to enable the public to participate in the creation of dance by using the multimedia interactive display system. The production of dance movements requires skilled dance techniques. According to computer information technology, the process of creating dance can be virtualized. Referring to a large number of excellent dance works, the classification and structure of elemental symbols, semantic expression, and design movements of dance are analyzed in detail respectively. Dance enthusiasts can experience the creation of dance by accessing the material in the database.

3)

Folk Dance Informatization-assisted Innovation Design Subsystem

Folk dance is as out of sync with modern life and technology as any other skill-based intangible cultural heritage. The information technology-assisted innovative design subsystem follows the time continuity of dance culture and combines the creation of dance works with information technology, not only to improve the innovation and efficiency of dance design, but also to help the dance culture integrate into the modern life, so that the dance culture can not only be preserved and inherited, but also be able to rely on information technology to develop.

4.4

Workflow of Digital Preservation of Folk Dance Art

The workflow of folk dance digital preservation is shown in Figure 5.

4.5

Analysis of the application effect of the platform for the protection and inheritance of dance art

4.5.1

Digital platform usability assessment

In order to verify the usability of the digital dance art preservation and inheritance platform, this section adopts the SUS scale, which has high confidence in the industry, for usability testing, and recruits a representative group of six folk dance artists to conduct the test. The SUS scale contains a total of ten questions, with five odd-numbered items for positive statements and five even-numbered items for negative statements, which are filled out by each of the six respondents at the end of the test. Table 1 shows the partial division of the SUM scale score levels. The scoring calculation rule is: the raw score of each odd-numbered item question (questions 1, 3, 5, 7, and 9) minus 1, 5 minus the raw score of each even-numbered item question (questions 2, 4, 6, 8, and 10), and since the score of each question ranges from 0 to 4 (with a maximum value of 40), and the score of the SUS scale ranges from 0 to 100, it is necessary to add up and multiply the final scores of each question by 2.5, in order to obtain a total score for the SUS scale.

Table 1.

The score of the SUM scale (part)

Grade	Rating	Percentage grade
84.1~100	A+	96~100
80.8~84	A	90~95
78.9~80.7	A-	85~89

The statistical results of the SUS scale for the six subjects are shown in Table 2. Based on the results of the scale filled out by the six subjects, the average score of 89.17 was calculated, and according to the score grading range of the SUS scale, 89.17 is rated as A+, which means that the digitalized folk dance art protection and inheritance platform constructed in this paper exceeds 96% of the platforms, with better usability and a higher degree of user satisfaction.

Table 2.

The SUS scale statistics of six participants

	Dancer 1	Dancer 2	Dancer 3	Dancer 4	Dancer 5	Dancer 6
Q 1	4	5	5	5	5	5
Q 2	1	1	1	2	1	1
Q 3	4	4	5	3	4	5
Q 4	1	1	2	1	1	1
Q 5	4	5	5	4	5	5
Q 6	3	3	1	1	2	1
Q 7	4	4	5	5	4	4
Q 8	1	1	2	1	1	1
Q 9	5	5	5	4	5	3
Q 10	1	2	2	1	2	1
Total score	85	87.5	92.5	87.5	90	92.5
Average score	89.17

4.5.2

Evaluation of the Communication Effectiveness of Ethnic Dance Arts

The digital platform designed in this paper is compared to the traditional way of distributing dance art. Invite 20 experts in folk dance art to evaluate the communication effect indicators set up in this paper, including “dissemination degree”, “influence degree”, “friendliness degree” and “interaction degree”. “Interaction”, which are labeled as evaluation indexes 1-4, totaling four levels, were evaluated. The weighting and analysis of the collected expert ratings is followed by calculating the average weighted rating of each indicator to obtain a comprehensive assessment of the communication effect of dance art.

The weighted rating results of each indicator are shown in Figure 6. From the figure, it can be seen that the experts are satisfied with the digital folk dance art protection and inheritance platform constructed in this paper in terms of “dissemination”, “influence”, “friendliness” and “interaction”. “Interactivity”, the weighted scores are 87.35, 84.05, 85.88 and 86.46, which are 5.21%~22.78% higher than the traditional way. That is to say, the platform constructed in this paper has a better effect on reflecting on the dissemination of folk dance art.

5

Conclusion

This paper utilizes digital technology to detect and extract the moving human body in folk dance, conducts human posture estimation, and evaluates the accuracy of digital technology in capturing dance movements. In addition, this paper designs a folk dance digital protection and inheritance platform, which builds a dance art protection database, digital resource sharing and multimedia dissemination system to provide effective digital technology for dance art protection and inheritance.

Dance artists have a relatively high evaluation of the “art inheritance effect” and “art protection effect” of digital technology, with recognition ratings of 4.70 and 4.44, respectively. The average accuracy of digital technology in capturing the standard movements of “left arm swing direction”, “left arm joint angle movement” and “left arm and torso angle” are 0.988, 0.986 and 0.984 respectively. The platform constructed in this paper surpasses more than 96% of other platforms and has better usability in protecting and preserving folk dance art. And experts rated this paper’s platform between 84.05 and 87.35 in terms of communication of dance art.

Language:: English

Publication timeframe:: 1 times per year
Journal Subjects:: Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other

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An Empirical Study on the Protection and Intelligent Inheritance Strategies of Folk Dance Art in the Digital Environment

Yaotian Li

Zhanguang Li

Published Online: Mar 19, 2025

Received: Oct 17, 2024

Accepted: Feb 04, 2025

DOI: https://doi.org/10.2478/amns-2025-0405

KeywordsDigital technology, Dance motion capture, Platform construction, SUS scale, Cultural preservation and heritage

© 2025 Yaotian Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
Digital technology, Dance motion capture, Platform construction, SUS scale, Cultural preservation and heritage