Virtual Human Technology Research Articles

Film and Television Animation Production Technology Based on Expression Transfer and Virtual Digital Human

The world of film and TV animation has witnessed a revolutionary transformation with the combination of Expression transfer and digital virtual Human technology. This paper delves into the superior methodologies and technological improvements in the discipline of animation production, especially specializing in how those technology are redefining the requirements and practices of animation in film and television. Expression transfer technology, a groundbreaking approach in animation, entails the transfer of facial expressions from real actors to lively characters. This technique not most effective enhances the realism of lively characters but additionally lets in for a extra nuanced and emotive performance, bridging the space among conventional animation and stay-action performances. Digital Human era, however, entails creating extraordinarily practical virtual representations of people. Those digital humans aren’t mere caricatures or stylized variations however are reasonable in appearance and movement, way to advancements in motion seize, 3-D modeling, and synthetic intelligence. The mixture of those technologies is main to a new technology in animation where characters aren’t only visually stunning however also exhibit a depth of emotion and realism previously unimaginable. This paper explores diverse case research and applications of these technology in current animation, highlighting their effect on storytelling, person improvement, and viewer engagement. It also addresses the demanding situations and moral considerations in employing these technologies, which includes retaining artistic integrity and the capacity for misuse. The research concludes with a forward-searching attitude on how Expression transfer and digital digital Human technologies are set to redefine the future of movie and television animation, presenting new opportunities for creative expression and narrative intensity.

Societal Perceptions and Acceptance of Virtual Humans: Trust and Ethics across Different Contexts

This article examines public perceptions of virtual humans across various contexts, including social media, business environments, and personal interactions. Using an experimental approach with 371 participants in the United Kingdom, this research explores how the disclosure of virtual human technology influences trust, performance perception, usage likelihood, and overall acceptance. Participants interacted with virtual humans in simulations, initially unaware of their virtual nature, and then completed surveys to capture their perceptions before and after disclosure. The results indicate that trust and acceptance are higher in social media contexts, whereas business and general settings reveal significant negative shifts post-disclosure. Trust emerged as a critical factor influencing overall acceptance, with social media interactions maintaining higher levels of trust and performance perceptions than business environments and general interactions. A qualitative analysis of open-ended responses and follow-up interviews highlights concerns about transparency, security, and the lack of human touch. Participants expressed fears about data exploitation and the ethical implications of virtual human technology, particularly in business and personal settings. This study underscores the importance of ethical guidelines and transparent protocols to enhance the adoption of virtual humans in diverse sectors. These findings offer valuable insights for developers, marketers, and policymakers to optimise virtual human integration while addressing societal apprehensions, ultimately contributing to more effective and ethical deployment of virtual human technologies.

Factors Associated With Pain Perception and Management Among Paediatric Nurses and Nursing Students Using Virtual Children: A Comparative Study.

To identify and compare factors associated with pain perception and management among paediatric nurses and nursing students using virtual human technology. This study employed a comparative, cross-sectional design. Fifty-one paediatric nurses from a tertiary hospital and 50 senior nursing students from a nursing college, both located in South Korea, participated in the study. Virtual vignettes, including scenarios with virtual children and their clinical information, were used to assess participants' pain perception and management. The virtual children, created from real face photos, varied in age (young/old), sex (boy/girl) and facial expressions (smile/grimace). Participants rated perceived pain scores and selected management choices for eight virtual vignettes, which were randomly presented. The Korean version of the Paediatric Nurses' Knowledge and Attitude Survey was completed along with demographic information. Both paediatric nurses and nursing students rated pain scores lower than the actual pain scores reported by virtual children. Nurses rated higher pain scores and accordingly selected more medication doses compared to students. Beyond pain-related knowledge, the facial expression of the virtual child influenced pain rating and medication choices, while age and sex had no effect. Nursing students were more sensitive to the facial expressions of virtual children when rating their pain compared to nurses. Future studies should explore how paediatric nurses' clinical experiences impact their assessment and management of child patient pain. Paediatric nurses' knowledge of pain is inadequate, necessitating ongoing education in pain management. Both nurses and nursing students should self-reflect on their pain assessment practices to ensure unbiased care regardless of child patients' characteristics. Virtual human technology can be utilised to train nurses and students to identify and address any biases in their assessment of patients' pain perception. STROBE checklist, cross-sectional. Digital face photos of four healthy children were used as the fundamental material for creating virtual children, with their parents' consent.

Virtual human on social media: Text mining and sentiment analysis

Virtual humans are embodied agents with a human-like appearance. Despite the recent booming development that has sparked widespread academic interest, how people perceive these seemingly human but entirely fictional creations remains unclear. To explore the status, trends, emotional tendencies, and focus of attention of the Chinese public towards virtual humans, this paper utilizes text mining techniques to collect and analyze popular posts related to virtual humans on Chinese social media. The results indicate that public discussions primarily focus on the technological and industrial development of virtual humans, applications in the fields of virtual idols and virtual streamers, and the corporate investment and policy development of virtual humans. Despite positive emotions dominating, there is an increasing trend in negative emotions. Concerns are related to service failures, the uncanny valley effect, ethical crises, and technological unemployment. The research findings contribute to policymakers, industry stakeholders, and the public in understanding the general attitudes toward virtual human technology, enabling informed decision-making.

Research on Human Computer Interaction Technology in Virtual Reality Scenes

This paper discusses the current status, challenges and development trends of human computer interaction technology in virtual reality scenarios. Virtual reality technology has gradually become a frontier field of human computer interaction research. This paper analyzes virtual reality technology and human computer interaction technology. By introducing the commonly used human computer interaction hardware equipment and software technology in current virtual reality scenarios, it reveals the actual application of human computer interaction in virtual reality environments. From the three aspects of technology, user experience, and security and privacy protection, this paper analyzes the challenges faced by human computer interaction technology in virtual reality scenarios. In the future, with the continuous advancement of technological innovation, new human-computer interaction technologies will continue to emerge, and the integration of artificial intelligence technology will further enhance the intelligence level of human-computer interaction, making the user interaction experience more natural and convenient.

The Long-cycle Elderly Care Service Model for Young People: A Case Study of Financial Elderly Care Services Based on Virtual Digital Human Technology

There is a lack of financial elderly care services for young people in China. Such services in traditional ways are unlikely to meet their future needs because of the decreasing workforce. Therefore, the current study aims to establish long-cycle financial elderly care services for young people through virtual digital human technology. Five young people are first interviewed about financial elderly care services; then, a survey is conducted for another sixty young people; after that, needs for financial elderly care services are extracted from the interview and the survey. Based on such needs, this study proposes a financial elderly service model built on design strategies including effective service touchpoints, clear communication, personalized service design, and immersive interaction, which is displayed on an App called REME. This model can be a reference for designing long-cycle elderly care systems.

Research on the Application of Virtual Reality Technology in Motor Skills Training

Abstract The emerging efficacy of Virtual Reality (VR) technologies in sports training is explored in this study. We developed a VR-based motor skill training model utilizing a markerless optical motion capture system. This system employs a domain adaptive detection method in the 3D human posture realm, enabling precise identification of motor action postural feature points in students. Subsequently, the model incorporates a human dynamic motion tracking function that minimizes computational errors in motion capture data, facilitating the implementation of multi-feature fusion-based virtual digital human body motion capture technology. An empirical analysis was conducted using H College University as the case study to evaluate the effectiveness of virtual motor skill training. The findings demonstrate that the average accuracy of the proposed method for recognizing body gestures achieved a significant level of 0.834, enabling more accurate identification of students’ motor action characteristics. Moreover, the post-test results of the VR class showed marked improvements, ranging from 0.56 to 15.56 points over traditional lecture classes and 0.43 to 10.33 points over video teaching classes. These substantial variances not only underline the superiority of the VR-based training model in enhancing academic interest and physical fitness but also in advancing motor skills among learners. The study accentuates VR’s potential to augment motor skills and foresees its expansive application in future motor training domains.

Exploring the Application of Computer Visual Arts in the Context of Digital Media

Abstract This paper provides an in-depth discussion on the critical technologies of computer visual arts in digital media, mainly focusing on virtual character modeling and human body tracking technologies. The study merges the models into the same coordinate system by combining point cloud data from different angles and calculating the transformation matrix. Accurate 3D human body models were reconstructed using point cloud alignment and fusion techniques. A particle filtering method combined color, motion and shape information for effective tracking. The experimental results show that the success rate of hand tracking reaches 95.35% in the case of no background interference, while the success rate is 90.97% in the environment with background interference. In addition, the study shows that low resolution images (584×388) outperform high resolution (968×676) in terms of tracking accuracy and speed. The study confirms that the combination of advanced computer vision techniques can effectively construct and follow virtual character models and realize high-precision human motion capture under different environmental conditions.

Speech-Driven Personalized Gesture Synthetics: Harnessing Automatic Fuzzy Feature Inference.

Speech-driven gesture generation is an emerging field within virtual human creation. However, a significant challenge lies in accurately determining and processing the multitude of input features (such as acoustic, semantic, emotional, personality, and even subtle unknown features). Traditional approaches, reliant on various explicit feature inputs and complex multimodal processing, constrain the expressiveness of resulting gestures and limit their applicability. To address these challenges, we present Persona-Gestor, a novel end-to-end generative model designed to generate highly personalized 3D full-body gestures solely relying on raw speech audio. The model combines a fuzzy feature extractor and a non-autoregressive Adaptive Layer Normalization (AdaLN) transformer diffusion architecture (DiTs-based). The fuzzy feature extractor harnesses a fuzzy inference strategy that automatically infers implicit, continuous fuzzy features. These fuzzy features, represented as a unified latent feature, are fed into the AdaLN transformer. The AdaLN transformer introduces a conditional mechanism that applies a uniform function across all tokens, thereby effectively modeling the correlation between the fuzzy features and the gesture sequence. This module ensures a high level of gesture-speech synchronization while preserving naturalness. Finally, we employ the diffusion model to train and infer various gestures. Extensive subjective and objective evaluations on the Trinity, ZEGGS, and BEAT datasets confirm our model's superior performance to the current state-of-the-art approaches. Persona-Gestor improves the system's usability and generalization capabilities, setting a new benchmark in speech-driven gesture synthesis and broadening the horizon for virtual human technology.

A virtual reality memory scene designed with memory reproduction as the concept

The use of VR (virtual reality) in memory recovery has considerable potential, and this is just beginning to materialize. Those exploratory studies conducted so far suggest that VR's participation will help improve the assessment of memory impairment and memory repair using recombinant techniques. Based on the current virtual reality technology is mostly used for game development, the relevant research on memory reproduction is relatively insufficient. In this paper, a memory gallery was built through 3D (three dimensional) modeling, and Metahuman technology was used to achieve character reproduction, combined with unreal5 development to achieve important memory reproduction. This work mainly uses 3D models to make a memory corridor, Metahuman digital virtual human technology and VR Chat VR social combination to bring users immersive precious memories reproduction, and can interact with it. Experiments have shown that recall reproduction is of great help to emotional repair. VR can help by making the presentation more immersive.

IVisit-Communicate for AEC Education: Using Virtual Humans to Practice Communication Skills in 360-Degree Virtual Field Trips

To prepare graduates for the dynamic and complex working environment in the architecture, engineering, and construction (AEC) industry, educational institutions have distinctly emphasized the significance of communication skills. Field trips are a widely utilized strategy to provide students with a situated learning setting where students can communicate with professionals onsite. However, several challenges limit the application of this strategy, and virtual field trips become a potential and promising supplement or alternative approach. This study discusses the pedagogical use of a virtual field trip experience augmented with conversational virtual humans—iVisit-Communicate—to produce realistic field trips for students to practice their communication skills. This virtual experience is supported by immersive computing (i.e., 360-degree virtual space) and conversational virtual human technologies. iVisit-Communicate simulates two types of communication to provide student-professional verbal communication opportunities: guided scenario and conversational scenario. The paper provides a detailed description of the technical and pedagogical development of iVisit-Communicate components followed by a student-centered experiment, focusing on measures such as system usability, sense of presence, and communication skills of students. The contribution of this study is to provide an in-depth understanding of the significance of integrating communication opportunities in virtual field trips and illustrate how such on-the-site opportunities successfully facilitate students’ communication practices.

Virtual Medical and Human‒Computer Interaction Technologies, Multidimensional Big Clinical and Biological Data, and Extended Digital Twin-based Medical Condition Diagnosis in the Healthcare Metaverse

Virtual Medical and Human‒Computer Interaction Technologies, Multidimensional Big Clinical and Biological Data, and Extended Digital Twin-based Medical Condition Diagnosis in the Healthcare Metaverse

A Survey on Big Data Technologies and Their Applications to the Metaverse: Past, Current and Future

The development of big data technologies, which have been applied extensively in various areas, has become one of the key factors affecting modern society, especially in the virtual reality environment. This paper provides a comprehensive survey of the recent developments in big data technologies, and their applications to virtual reality worlds, such as the Metaverse, virtual humans, and digital twins. The purpose of this survey was to explore several cutting-edge big data and virtual human modelling technologies, and to raise the issue of future trends in big data technologies and the Metaverse. This survey investigated the applications of big data technologies in several key areas—including e-health, transportation, and business and finance—and the main technologies adopted in the fast-growing virtual world sector, i.e., the Metaverse.

Tailoring Recruitment Communication using Virtual Human Technology to Increase Participation of Older Minority Adults in Clinical Trials

AbstractBackgroundOlder adult minorities are an underserved population, who are at a particularly high risk for developing chronic health conditions and are significantly underrepresented in clinical research. Well‐known barriers, including research‐related mistrust (e.g., belief that participants lack choice, mistrust of white researchers), complicated messaging, lack of cultural diversity/sensitivity among clinical trials staff, and the exclusion of decisional support providers in decision‐ making could impede older adult minority participation in clinal trials.Tailoring content and source preferences to be patient‐ centered, culturally sensitive (i.e., promote feelings of comfort, trust, respect), simple to understand, and personally relevant to the receivers (patients and caregivers) has been linked to positive health behaviors among older adult minorities. Additionally, tailoring is critical to improving comprehension, clear and complete understanding of the messaging. However, tailoring has not been systematically studied as a strategy to increase clinical trial participation rates of older adult minorities, including those with cognitive challenges. Our long‐term goal is to increase clinical trial participation among older adult minorities (Black/African American, Hispanic/Latinx, and/or rural adults over the age of 50) using virtual human technology (VHT). Specifically, we are using community‐based participatory research principles to develop virtual humans that can interact with receivers to deliver tailored intervention content.MethodIn Aim 1, we will conduct focus groups with older adult minorities to redesign ALEX to develop culturally sensitive messages designed specifically for older adults, including those with subjective cognitive difficulties. In Aim 2, we will disseminate the intervention and track engagement of older adult minority participants into active, NIH‐funded clinical trials across different modalities for remotely delivering ALEX. In Aim 3, we will compare whether using ALEX to deliver interactive and tailored clinical trial content is more effective than standard (e.g., static) recruitment materials for enrolling older minorities into NIH‐funded clinical trials.ResultWe will describe patient and caregiver preferences for intervention modality and content.ConclusionAchievement of these project aims is expected to result in an adaptable, minimally tailored VHT recruitment intervention for increasing older adult minority participation rates in active NIH‐funded clinical trials.

Case report: Quantitative recognition of virtual human technology acceptance based on efficient deep neural network algorithm.

With the advancement of artificial intelligence, robotics education has been a significant way to enhance students' digital competency. In turn, the willingness of teachers to embrace robotics education is related to the effectiveness of robotics education implementation and the sustainability of robotics education. Two hundred and sixty-nine teachers who participated in the "virtual human education in primary and secondary schools in Guangdong and Henan" and the questionnaire were used as the subjects of study. UTAUT model and its corresponding scale were modified by deep learning algorithms to investigate and analyze teachers' acceptance of robotics education in four dimensions: performance expectations, effort expectations, community influence and enabling conditions. Findings show that 53.68% of the teachers were progressively exposed to robotics education in the last three years, which is related to the context of the rise of robotics education in schooling in recent years, where contributing conditions have a direct and significant impact on teachers' acceptance of robotics education. The correlation coefficients between teacher performance expectations, effort expectations, community influence, and enabling conditions and acceptance were 0.290 (p = 0.000<0.001), -0.144 (p = 0.048<0.05), 0.396 (p = 0.000<0.001), and 0.422 (p = 0.000<0.001) respectively, indicating that these four core dimensions both had a significant effect on acceptance. Optimization comparison results of deep learning models show that mDAE and AmDAE provide a substantial reduction in training time compared to existing noise-reducing autoencoder models. It is shown that time-complexity of the deep neural network algorithm is positively related to the number of layers of the model.

Application and Visualization of Human 3D Anatomy Teaching for Healthy People Based on a Hybrid Network Model.

With the development of computer technology, information technology, and 3D reconstruction technology of the medical human body, 3D virtual digital human body technology for human health has been widely used in various fields of medicine, especially in teaching students of application and anatomy. Its advantage is that it can view 3D human anatomy models from any angle and can be cut in any direction. In this paper, we propose an improved algorithm based on a hybrid density network and an element-level attention mechanism. The hybrid density network is used to generate feasible hypotheses for multiple 3D poses, solve the ambiguity problem in pose reasoning from 2D to 3D, and improve the performance of the network by adding the AReLU function combined with an element-wise attention mechanism. Teaching students in anatomy makes students' learning more convenient and teachers' teaching explanations more vivid. Comparative experiments show that the accuracy of 3D human pose estimation using a single image input is better than the other two-stage methods.

Finding the Existence and Identity of the Person Depicted in Computer Graphics: The CG Child Pornography Case and Its Implications for Deepfake and Virtual Human Technologies

Finding the Existence and Identity of the Person Depicted in Computer Graphics: The CG Child Pornography Case and Its Implications for Deepfake and Virtual Human Technologies

Development of a Credible Virtual Clinician Promoting Colorectal Cancer Screening via Telehealth Apps for and by Black Men: Qualitative Study.

BackgroundTraditionally, promotion of colorectal cancer (CRC) screening among Black men was delivered by community health workers, patient navigators, and decision aids (printed text or video media) at clinics and in the community setting. A novel approach to increase CRC screening of Black men includes developing and utilizing a patient-centered, tailored message delivered via virtual human technology in the privacy of one’s home.ObjectiveThe objective of this study was to incorporate the perceptions of Black men in the development of a virtual clinician (VC) designed to deliver precision messages promoting the fecal immunochemical test (FIT) kit for CRC screening among Black men in a future clinical trial.MethodsFocus groups of Black men were recruited to understand their perceptions of a Black male VC. Specifically, these men identified source characteristics that would enhance the credibility of the VC. The modality, agency, interactivity, and navigability (MAIN) model, which examines how interface features affect the user’s psychology through four affordances (modality, agency, interactivity, and navigability), was used to assess the presumed credibility of the VC and likability of the app from the focus group transcripts. Each affordance triggers heuristic cues that stimulate a positive or a negative perception of trustworthiness, believability, and understandability, thereby increasing source credibility.ResultsIn total, 25 Black men were recruited from the community and contributed to the development of 3 iterations of a Black male VC over an 18-month time span. Feedback from the men enhanced the visual appearance of the VC, including its movement, clothing, facial expressions, and environmental surroundings. Heuristics, including social presence, novelty, and authority, were all recognized by the final version of the VC, and creditably was established. The VC was named Agent Leveraging Empathy for eXams (ALEX) and referred to as “brother-doctor,” and participants stated “wanting to interact with ALEX over their regular doctor.”ConclusionsInvolving Black men in the development of a digital health care intervention is critical. This population is burdened by cancer health disparities, and incorporating their perceptions in telehealth interventions will create awareness of the need to develop targeted messages for Black men.

Physical Education Teaching in Colleges and Universities Assisted by Virtual Reality Technology Based on Artificial Intelligence

Virtual reality technology has promoted the reform of education. This research mainly discusses college physical education teaching assisted by artificial intelligence-based virtual reality technology. According to the position change of the virtual human’s center of gravity, the spline keyframe interpolation method is used for interpolation, and the model pose obtained in each frame is rendered to obtain the virtual human’s animation. After synthesizing a virtual human animation with three-dimensional human motion data, the animation can have functions such as video storage, fast playback, slow playback, and freeze. At the same time, the system can also display and play the virtual human animation and the video shot by the camera on the same screen, in order to make an intuitive comparison of the athletes’ movements. Coaches can edit by hand or shoot the sports of outstanding domestic and foreign athletes on the spot and then use VC++6.0 as a development tool to analyze and get the simulation video of the 3D virtual human body. The virtual human animation technology in the motion analysis system is to relocate the three-dimensional motion data extracted from the video captured by the camera to the three-dimensional virtual human model we have established, and the three-dimensional virtual human will then simulate the technical actions of the athletes, which indirectly reflects that the three-dimensional movement information of the athletes enables coaches and athletes to observe the athletes’ technical movements in a three-dimensional space in real time, repeatedly, and from multiple angles so that the coach can accurately guide the athletes’ technical movements. Finally, a neural network based on artificial intelligence technology is used to evaluate the teaching effect. In the comparative experiment, 35% of the people in the virtual teaching experiment group were excellent, while the control group had only 10% in this excellent range (90–100). This research contributes to the smooth progress of VR technology teaching in colleges and universities.

Using Virtual Human Technology in Perioperative Team Training Simulations.

Incorporating virtual human (VH) technology into simulation programs for perioperative education and training can improve interdisciplinary teamwork and communication. The development of VHs allowed interdisciplinary teams at the University of Florida Health Shands Hospital to overcome obstacles during training, such as communication gaps. A multidisciplinary team that included perioperative leaders and quality specialists developed three scenarios for interdisciplinary training to provide participants with the opportunity to practice their communication skills and improve patient safety. Using validated tools to promote standardized communication, participants had to address patient safety concerns assertively during the simulations. After each simulation session, quality specialists conducted a debriefing, collected data via surveys, and identified areas for improvement. As a result of the VH simulation sessions, perioperative staff members reported increased confidence and competence when providing patient care. Using VHs to enhance education is an innovative strategy that is useful for both novice and experienced perioperative nurses.