Making of The Heretic: Digital Human tech package

Creating a realistic human is a complex technical challenge, as you need a huge amount of data to achieve a high level of visual fidelity.When working on The Heretic, the Demo Team developed tools to overcome many problems related to facial animation; attaching hair to skin; and eye, teeth and skin rendering in Unity. Those tools are now available on GitHub. Read on for a full technical breakdown of the process behind these solutions.

My name is Lasse Jon Fuglsang Pedersen, and I am a Senior Software Engineer on the Unity Demo Team. During the production of The Heretic, one of the things I worked on is the set of technical solutions that drive the face of Gawain, the digital human in the film.

This work was recently released as a standalone package on GitHub. In this blog post I will discuss some of the features of the package and share some insights into the development process behind those features.

Facial animation

One of the goals for the digital human in The Heretic was to attempt to avoid the uncanny valley in terms of facial animation, while still taking a realistic approach to the character as a whole. To match the actor’s performance as closely as possible, we decided to try using 4D capture data (a 3D scan per frame of animation) for the animation of the face mesh, which would then at least have the potential to be geometry-accurate to the actor’s facial performance (where not obstructed).

Using 4D capture data brought many interesting new challenges, as Krasimir Nechevski, our animation director, explains in more detail in this previous blog post. A lot of effort went into figuring out how to process and tweak the captured data, and then actually doing that, to get it into a state that we were happy with for the film.

Notes on processing

As an example, one of the issues we had was related to the geometry of the eyelids. Because eyelashes partially obstructed the eyelids during capture, the captured data also contained some influence from eyelashes, which manifested itself as noise in those regions. As a result, the geometry of the eyelids was inaccurate and jittery, and this meant that we had to find a way to reconstruct the geometry in those regions.

Jittery geometry near the eyelids

The issue with the eyelid geometry was apparent quite early in the process, so as part of working on the importer for just getting the data into Unity, we also experimented with region-specific noise reduction and reconstruction, using differential mesh processing techniques. Specifically, we would perform noise reduction by smoothing the regional change in curvature over time, and we would perform reconstruction by transplanting the curvature of a (clean) base mesh onto each damaged region of each frame of the captured sequence.

Denoising and transplanting geometry near the eyelids

While the results were fairly robust, we felt they were unfortunately also a bit too synthetic when compared to the original data: The eyelids, while more stable, lost some of the original motion that effectively made them feel human. It became clear that we needed a middle ground, which might have required more research than we realistically had time for. So when an external vendor offered to tackle the reconstruction work, that was an easy choice.

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