Photorealistic avatars have become essential for immersive applications in virtual reality (VR) and augmented reality (AR), enabling lifelike interactions in areas such as training simulations, telemedicine, and virtual collaboration. These avatars bridge the gap between the physical and digital worlds, improving the user experience through realistic human representation. However, existing avatar creation techniques face significant challenges, including high costs, long creation times, and limited utility in virtual applications. Manual methods, such as MetaHuman, require extensive time and expertise, while automatic approaches, such as NeRF-based pipelines often lack efficiency, detailed facial expression fidelity, and are unable to be rendered at a speed sufficent for real-time applications. By involving several cutting-edge modern techniques, we introduce an end-to-end 3D Gaussian Splatting (3DGS) avatar creation pipeline that leverages monocular video input to create a scalable and efficient photorealistic avatar directly compatible with the Unity game engine. Our pipeline incorporates a novel Gaussian splatting technique with customized preprocessing that enables the user of ”in the wild” monocular video capture, detailed facial expression reconstruction and embedding within a fully rigged avatar model. Additionally, we present a Unity-integrated Gaussian Splatting Avatar Editor, offering a user-friendly environment for VR/AR application development. Experimental results validate the effectiveness of our preprocessing pipeline in standardizing custom data for 3DGS training and demonstrate the versatility of Gaussian avatars in Unity, highlighting the scalability and practicality of our approach.
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Immersive Commodity Telepresence with the AVATRINA Robot Avatar
Immersive robotic avatars have the potential to aid and replace humans in a variety of applications such as telemedicine and search-and-rescue operations, reducing the need for travel and the risk to people working in dangerous environments. Many challenges, such as kinematic differences between people and robots, reduced perceptual feedback, and communication latency, currently limit howwell robot avatars can achieve full immersion. This paper presents AVATRINA, a teleoperated robot designed to address some of these concerns and maximize the operator’s capabilities while using a commodity light-weight human–machine interface. Team AVATRINA took 4th place at the recent $10 million ANA Avatar XPRIZE competition, which required contestants to design avatar systems that could be controlled by novice operators to complete various manipulation, navigation, and social interaction tasks. This paper details the components of AVATRINA and the design process that contributed to our success at the competition. We highlight a novel study on one of these components, namely the effects of baseline-interpupillary distance matching and head mobility for immersive stereo vision and hand-eye coordination.
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- Award ID(s):
- 2025782
- PAR ID:
- 10486597
- Publisher / Repository:
- Springer
- Date Published:
- Journal Name:
- International Journal of Social Robotics
- ISSN:
- 1875-4791
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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