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arXiv 2502.08085cs.GR
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3D面部化身的交互式全息可视化

Interactive Holographic Visualization for 3D Facial Avatar

Tri Tung Nguyen Nguyen, Fujii Yasuyuki, Dinh Tuan Tran, Joo-Ho Lee

AI总结:

针对医学培训中传统面部表情可视化方法低效的问题,提出基于3D交互式面部化身的全息可视化平台,整合3D高斯溅射与实时校准,为疼痛评估练习提供更沉浸真实的模拟体验。

摘要:

传统的动态人类表情可视化方法(尤其是在医学培训中)常依赖平板显示器或静态人体模型,经证实其在真实模拟方面效率低下。为此,我们提出一个平台,利用能显示非语言反馈(包括疼痛信号)的3D交互式面部化身。该化身被投射到立体、视点相关的3D显示器上,为疼痛评估练习提供更具沉浸感和真实感的模拟患者体验。但目前尚无实时动态预测和投射交互式3D面部化身的解决方案。为解决此问题,我们强调需要能全息投射面部化身的3D显示投影系统,让用户可从任意视点与化身交互。通过整合3D高斯溅射(3DGS)和实时视点相关校准,我们显著改善了疼痛识别与评估培训环境。

英文摘要:

Traditional methods for visualizing dynamic human expressions, particularly in medical training, often rely on flat-screen displays or static mannequins, which have proven inefficient for realistic simulation. In response, we propose a platform that leverages a 3D interactive facial avatar capable of displaying non-verbal feedback, including pain signals. This avatar is projected onto a stereoscopic, view-dependent 3D display, offering a more immersive and realistic simulated patient experience for pain assessment practice. However, there is no existing solution that dynamically predicts and projects interactive 3D facial avatars in real-time. To overcome this, we emphasize the need for a 3D display projection system that can project the facial avatar holographically, allowing users to interact with the avatar from any viewpoint. By incorporating 3D Gaussian Splatting (3DGS) and real-time view-dependent calibration, we significantly improve the training environment for accurate pain recognition and assessment.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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