实时,单摄像头,数字化人类发展

Douglas Roble, Darren Hendler, Jeremy Buttell, Melissa Cell, Jason Briggs, Chad Reddick, Lonnie Iannazzo, Deer Li, Mark Williams, Lucio Moser, Cydney Wong, Dimitry Kachkovski, Jason Huang, Kai Zhang, David A. McLean, Rickey Cloudsdale, D. Milling, Ron Miller, JT Lawrence, Chinyu Chien
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引用次数: 4

摘要

我们已经建立了一个实时(60 fps)逼真的面部动作捕捉系统,该系统使用单个相机,专有的深度学习软件和虚幻引擎4来创建照片真实的数字人类和生物。我们的系统使用数千帧真实捕获的演员3D面部表演(由自动离线系统生成),而不是传统的基于facs的面部rig来生成演员面部移动的准确模型。这些3D数据用于创建实时机器学习模型,该模型使用单个图像在17毫秒内准确描述准确的面部姿势。面部运动是高度逼真的,包括基于区域的血液流动,皱纹激活和孔隙结构变化,由几何变形实时驱动。演员的面部表现可以以极高的保真度转移到角色身上,并且切换机器学习模型是即时的。我们认为这是在开发中的其他实时虚拟角色项目的重大进步。在我们的实时面部动画技术的基础上,我们寻求使与我们的化身互动更加身临其境和情感。我们为驾驶人类/角色的演员建立了一个AR系统,让他们在VR中看到并与人互动,或者在AR中观看的其他人。通过这种技术,你在VR中与之互动的角色可以进行正确的眼神交流,在你周围走动,并像你们在一起一样互动,同时仍然达到最高质量的捕捉。这一过程使得VR / AR体验比其他任何系统都更加有形。我们的另一个目标是以最小的延迟实现照片真实的虚拟化身远程呈现。我们已经能够成功地将我们的数字人从洛杉矶的办公室实时驱动到温哥华的办公室。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time, single camera, digital human development
We have built a real-time (60 fps) photo-realistic facial motion capture system which uses a single camera, proprietary deep learning software, and Unreal Engine 4 to create photo-real digital humans and creatures. Our system uses thousands of frames of realistic captured 3D facial performance of an actor (generated from automated offline systems) instead of a traditional FACS-based facial rig to produce an accurate model of how an actor's face moves. This 3D data is used to create a real-time machine learning model which uses a single image to accurately describe the exact facial pose in under 17 milliseconds. The motion of the face is highly realistic and includes region based blood flow, wrinkle activation, and pore structure changes, driven by geometry deformations in real-time. The facial performance of the actor can be transferred to a character with extremely high fidelity, and switching the machine learning models is instantaneous. We consider this a significant advancement over other real-time avatar projects in development. Building on top of our real-time facial animation technology, we seek to make interaction with our avatars more immersive and emotive. We built an AR system for the actor who is driving the human / character to see and interact with people in VR or others viewing in AR. With this technique, the character you are interacting with in VR can make correct eye contact, walk around you, and interact as if you were together all while still achieving the highest quality capture. This process allows for a much more tangible VR / AR experience than any other system. Another goal of ours is to achieve photo-real avatar telepresence with minimal latency. We have been able to successfully live-drive our digital humans from our office in Los Angeles to our office in Vancouver.
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