A Scalability Benchmark for a Virtual Audience Perception Model in Virtual Reality

Glémarec, Yann; Bosser, Anne-Gwenn; Buche, Cédric; Lugrin, Jean-Luc; Landeck, Maximilian; Latoschik, Marc Erich; Chollet, Mathieu

doi:10.1145/3359996.3364784

Cited by 4 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the system is flexible and allows for agents from different 3D Character Modeling tools, which can be placed in a variety of configurations and play stand-up animations. More details on the modules implementation within the game engine and the combination and blending mechanism for the animations can be found in Glémarec et al (2020) but without further information on our rules based approach which is a new contribution.…”

Section: System's Structurementioning

confidence: 99%

Indifferent or Enthusiastic? Virtual Audiences Animation and Perception in Virtual Reality

Glémarec¹,

Lugrin²,

Bosser³

et al. 2021

Front. Virtual Real.

Self Cite

View full text Add to dashboard Cite

In this paper, we present a virtual audience simulation system for Virtual Reality (VR). The system implements an audience perception model controlling the nonverbal behaviors of virtual spectators, such as facial expressions or postures. Groups of virtual spectators are animated by a set of nonverbal behavior rules representing a particular audience attitude (e.g., indifferent or enthusiastic). Each rule specifies a nonverbal behavior category: posture, head movement, facial expression and gaze direction as well as three parameters: type, frequency and proportion. In a first user-study, we asked participants to pretend to be a speaker in VR and then create sets of nonverbal behaviour parameters to simulate different attitudes. Participants manipulated the nonverbal behaviours of single virtual spectator to match a specific levels of engagement and opinion toward them. In a second user-study, we used these parameters to design different types of virtual audiences with our nonverbal behavior rules and evaluated their perceptions. Our results demonstrate our system’s ability to create virtual audiences with three types of different perceived attitudes: indifferent, critical, enthusiastic. The analysis of the results also lead to a set of recommendations and guidelines regarding attitudes and expressions for future design of audiences for VR therapy and training applications.

show abstract

Section: System's Structurementioning

confidence: 99%

Indifferent or Enthusiastic? Virtual Audiences Animation and Perception in Virtual Reality

Glémarec¹,

Lugrin²,

Bosser³

et al. 2021

Front. Virtual Real.

Self Cite

View full text Add to dashboard Cite

show abstract

“…For systems handling many users, either interacting independently or in direct or indirect collaboration to complete a common task, scalability is understood as the capacity to accommodate for more users. In Glemarec et al [34], the main challenge is to handle multiple user sessions at once: the problem size here is the number of users, while the effort variable is the system performance in terms of latency. In Deng et al [35], the challenge is to collect a large training set of images with labels indicating the presence or absence of a set of objects of interest, by querying humans on a crowdsourcing platform.…”

Section: Non-stereotypical and Composite Scenariosmentioning

confidence: 99%

Scalability in Visualization

Richer¹,

Pister

Abdelaal

et al. 2024

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

We introduce a conceptual model for scalability designed for visualization research. With this model, we systematically analyze over 120 visualization publications from 1990 to 2020 to characterize the different notions of scalability in these works. While many papers have addressed scalability issues, our survey identifies a lack of consistency in the use of the term in the visualization research community. We address this issue by introducing a consistent terminology meant to help visualization researchers better characterize the scalability aspects in their research. It also helps in providing multiple methods for supporting the claim that a work is "scalable." Our model is centered around an effort function with inputs and outputs. The inputs are the problem size and resources, whereas the outputs are the actual efforts, for instance, in terms of computational run time or visual clutter. We select representative examples to illustrate different approaches and facets of what scalability can mean in visualization literature. Finally, targeting the diverse crowd of visualization researchers without a scalability tradition, we provide a set of recommendations for how scalability can be presented in a clear and consistent way to improve fair comparison between visualization techniques and systems and foster reproducibility.

show abstract

“…Focusing on public speaking tasks in various fields and a virtual environment with an interactive virtual audience (i.e., providing nonverbal feedback) has been the focus of several studies (Batrinca et al, 2013; Chollet & Scherer, 2017; Chollet et al, 2016a, 2016b, 2021; Glemarec et al, 2019; Kang et al, 2016; Lugrin et al, 2016; Seufert et al, 2022). Virtual reality allows public speakers to practice in a situation very similar to what they will face in real life.…”

Section: Introductionmentioning

confidence: 99%

Perception of avatars nonverbal behaviors in virtual reality

Etienne,

Leclercq,

Remacle

et al. 2023

Psychology and Marketing

View full text Add to dashboard Cite

Virtual reality has shown great potential in many fields, especially in business and psychology. By immersing someone in a new computer‐generated reality, it is possible to create realistic, safe, and controllable simulations for research and training, as well as new three‐dimensional‐enriched consumer experiences and services. Most of these environments, especially in the metaverse, rely on virtual representations of people called avatars. The design and non‐verbal behaviors of these avatars must be carefully crafted to provide a realistic and truly immersive experience. This paper aims to understand how avatar nonverbal behaviors (i.e., body posture, facial expression, and head movement) are perceived by users immersed in a virtual reality context, a very common situation encountered in many simulations and especially during training. Therefore, the first objective of this study is to validate, through an experiment with 125 participants, how the audience's levels of emotional valence and arousal are perceived in virtual reality. Based on these results, a library of audience non‐verbal behaviors corresponding to different arousal and valence levels is now available for future applications. The experiment also examines the benefits of using low‐end versus high‐end virtual reality headsets, and photo‐realistic versus cartoon avatars. The results have implications for the design of realistic, challenging, and interactive virtual audiences.

show abstract

A Scalability Benchmark for a Virtual Audience Perception Model in Virtual Reality

Cited by 4 publications

References 5 publications

Indifferent or Enthusiastic? Virtual Audiences Animation and Perception in Virtual Reality

Indifferent or Enthusiastic? Virtual Audiences Animation and Perception in Virtual Reality

Scalability in Visualization

Perception of avatars nonverbal behaviors in virtual reality

Contact Info

Product

Resources

About