윤보람

Development of Open XR platform for high immersive collaboration

As avatars have evolved from simple digital representations into extensions of our identities, they offer unprecedented opportunities for self-expression and customization beyond the physical world limitations. While virtual platforms foster new forms of identity exploration, social norms still play a crucial role in defining what is considered appropriate in these environments. In this study, we surveyed 150 participants to investigate social norms surrounding avatar modifications, examining how perspectives, contexts, and personality traits influence attitudes toward appropriateness. Our findings reveal that avatar modifications are generally viewed as more appropriate when considered from a partner's perspective, especially for changeable attributes. However, these modifications are perceived as less acceptable in professional settings such as workplaces. Additionally, individuals with high self-monitoring tendencies tend to be more resistant to changes, while those scoring higher on Machiavellianism are more accepting of changes, particularly regarding unchangeable attributes and emotional expressions. These findings provide valuable insights for platform developers and designers, highlighting the importance of implementing context-aware customization options that balance core identity elements with personality-driven preferences, thereby enhancing user experiences while respecting social norms.

Understanding gender differences in facial and spatial recognition is crucial for enhancing avatar-mediated communication. However, there remains a gap in understanding how participant gender influences perceptions of avatar facial expressions and spatial dynamics in Mixed Reality communication. Therefore, our study investigates how avatar non-verbal cues interact with gender differences to affect user experience and understanding in MR environments. To examine these complex relationships, we conducted a user study comparing the effects of various avatar facial expressions (Full, Mouth-Only, and Emotion-based) and interpersonal distances (Closer vs. Farther) on facial animation realism and social presence, with a focus on gender-balanced participant groups. Our findings revealed that female participants were particularly sensitive to the avatar’s proximity and facial expressions, reporting significantly higher perceptions of facial animation realism, copresence, message understanding, and affective understanding at farther distances compared to male participants. They also perceived higher copresence and message understanding when exposed to emotion-based facial expressions, as opposed to a mouth-only condition-a distinction not observed among male participants. Based on our findings, we advocate for avatar design strategies that accommodate gender differences in perception and preference, potentially through customizable levels of expressiveness to cater to diverse user needs and contexts.

We propose a system concept for Augmented Reality Head-Mounted Display users, which supports multitask viewing with multiple vir-tual workspaces anchored in the real-world space. Although people encounter multitasking necessities frequently, the native AR HMD and existing interfaces lack measures to visualize multiple sets of spatially-anchored information in parallel. The system separately vi-sualizes two different sets of spatially-anchored information, one on each AR HMD and smartphone, enabling side-by-side multitasking on AR HMD without applying heavy load on users. We implemented a proof-of-concept prototype that allows side-by-side viewing of the two different virtual workspaces. The proposed concept shows promises of multitasking on AR HMD, and future research will de-velop the system to be fully functional and verified with user studies.

This study explored how avatar face Level of Detail (LOD) and task types affect users' social presence and interpersonal communication in Augmented Reality remote collaboration. In AR remote collaboration, users are represented as avatars, and an actual user's appearance inevitably changes. While certain situations require an avatar that resembles a user, it is challenging to reconstruct everything realistically due to its high cost. Since facial parts show relative significance compared to body parts, we proposed controlling face LOD as an approach to lowering the cost while maintaining social presence in AR environments. Our results showed that while Mid-LOD maintains social presence but reduces costs compared to High-LOD, Low-LOD negatively impacts social presence mainly due to emotional understanding. Based on our findings, we highlight the importance of 1) considering facial expressions and emotional understanding in managing face LOD, 2) figuring out the collaboration context with different effects of tasks and communication behaviors, and 3) providing additional communication cues for maintaining social presence while lowering the cost.

We present a user interface method called TranSlider, designed for an AR collaboration with the concept of customized visualization of the user-selected augmented content. In AR, virtual content is augmented on top of the real world, so collaborating users are inevitably exposed to the diverse-overlapped information layers. Because the human recognition system has limited capacity, this overloaded information may burden the user to understand fully, and it is also challenging to manipulate among occluded objects. To solve this issue, we designed the TranSlider that allows users to control the presence of augmented content being transparent or highlighted based on the user interaction. The implemented prototype includes UI components, a manipulation function, and a network-connected collaboration module, and its applicability was verified through a preliminary interview. We expect that it would effectively support general AR collaborations and those with specific purposes, such as designing complex, hierarchical, or made up of many partial assets.

This study investigates the effects of a virtual hand representation on the user experience including social presence during hand-based 3D remote collaboration. Although a remote hand appearance is a critical parts of a hand-based telepresence, it has been rarely studied in comparison to studies on the self-embodiment of virtual hands in a 3D environment. Thus, we conducted a user study comparing the three virtual hands models (Skeleton, Low Polygon and Realistic) while performing a remote collaborative task based on the American Sign Language (ASL) using both Augmented Reality (AR) and Virtual Reality (VR) environments. We found that the realistic type was perceived as the most sense of being together, human-like, and trustable representation. The low polygon model could also convey a clear sign and moderate level of social presence. Although the system was configured asymmetrically in AR and VR, little difference in perception was found except for the participant's mental load and message understanding. We then discuss the results and suggest design implications for future hand-based 3D telepresence systems.