Untact 실감형 OpenXR 플랫폼 기술 개발

We propose OFERA, a novel framework for real-time expression control of photorealistic Gaussian head avatars for VR headset users. Existing approaches attempt to recover occluded facial expressions using additional sensors or internal cameras, but sensor-based methods increase device weight and discomfort, while camera-based methods raise privacy concerns and suffer from limited access to raw data. To overcome these limitations, we leverage the blendshape signals provided by commercial VR headsets as expression inputs. Our framework consists of three key components: (1) Blendshape Distribution Alignment (BDA), which applies linear regression to align the headset-provided blendshape distribution to a canonical input space; (2) an Expression Parameter Mapper (EPM) that maps the aligned blendshape signals into an expression parameter space for controlling Gaussian head avatars; and (3) a Mapper-integrated Avatar (MiA) that incorporates EPM into the avatar learning process to ensure distributional consistency. Furthermore, OFERA establishes an end-to-end pipeline that senses and maps expressions, updates Gaussian avatars, and renders them in real-time within VR environments. We show that EPM outperforms existing mapping methods on quantitative metrics, and we demonstrate through a user study that the full OFERA framework enhances expression fidelity while preserving avatar realism. By enabling real-time and photorealistic avatar expression control, OFERA significantly improves telepresence in VR communication. A project page is available at https://ysshwan147.github.io/projects/ofera/.

We present a VR research demo for practical telepresence with photorealistic 3D Gaussian Splatting (3DGS) avatars under HMD-only sensing. The demo consists of two parts that provide complementary experiences in a single session: a face part, where HMD-provided blendshape signals drive an expressive 3DGS head avatar rendered stereoscopically on the client, and a full-body part, where a user-specific 3DGS full-body avatar is created from a single image and driven using HMD signals. During the demo, participants first capture a single image for full-body avatar creation, experience facial control using a pre-built third-person head avatar while the full-body avatar is generated, and then control their personalized full-body avatar in VR. By enabling both facial and full-body controllability and contrasting two rendering-responsibility designs, client-side direct 3D rendering and server-side stereoscopic image rendering/streaming-the demo offers practical insights for designing responsive, realistic VR telepresence systems under HMD-only sensing.

We investigate how path context, encompassing both comfort and attractiveness, shapes user experiences in outdoor locative storytelling using Augmented Reality (AR). Addressing a research gap that predominantly concentrates on indoor settings or narrative backdrops, our user-focused research delves into the interplay between perceived path context and locative AR storytelling on routes with diverse walkability levels. We examine the correlation and causation between narrative engagement, spatial presence, perceived workload, and perceived path context. Our findings show that on paths with reasonable path walkability, attractive elements positively influence the narrative experience. However, even in environments with assured narrative walkability, inappropriate safety elements can divert user attention to mobility, hindering the integration of real-world features into the narrative. These results carry significant implications for path creation in outdoor locative AR storytelling, underscoring the importance of ensuring comfort and maintaining a balance between comfort and attractiveness to enrich the outdoor AR storytelling experience.