The Anatomical Deer

Christopher Macwana


About the Project

The Anatomical Deer was created by Barajoun Entertainment's Lead Creature TD and dedicated VFX artists, Christopher Macawna. With over 16 years of creature rigging experience, Macwana wanted to challenge his technical and creative capabilities by simulating his first anatomical, muscle-driven creature using Ziva VFX, from scratch. Chris chose the deer for their naturally thin skin and short fur which could highlight the intricate muscle system and its many subtle nuances.

Getting STarted

Chris started The Anatomical Deer by sculpting the full anatomy model. To achieve the highest level of detail while maintaining a modest and practical timeline, he tactfully chose to merge smaller muscle clusters together. This strategy shaved off critical simulation time by reducing the number of necessary attachments and minimizing the overall scene complexity. Simplifying anatomical models is a great way to balance time and realism. Throughout the process, Chris turned to the Ziva Community for support, feedback, and more speed tips.

Chris then simulated three different anatomy layers; the muscles, the fat, and an added skin layer for increased winkles. According the Chris, the actual muscle setup was very straight forward. He was able to adjust his integrators to achieve varying muscle mass effects and relied on Ziva Sub-Tissues to help stabilize the Deer's thinner muscles. Ziva Mesh Checks were run throughout this process to ensure the topology was all smooth and intersection-free, at all times.

"I was curious about Ziva from the very start. It is the first plugin that brings every critical element of the workflow together. I never liked having to jump around to use Maya's muscle system, soft body etc. And in addition to a centralized system, it also allowed me to enhance my creative abilities. From a workflow perspective, Ziva's a no-brainer."

Christopher Macwana, Lead Creature TD, Barajoun Entertainment

Using Ziva Vfx

According to Chris, the fat pass was the most challenging element of the simulation. The procedural nature of anatomical simulations required a level of harmony between the model and the final rig that Chris had not encountered before. As such, he needed to make minor adjustments to his initial fat model. He then made use of a number of Ziva parameters, including collisionPointSpacing, contactStiffness and inertialDamping to get the exact results he envisioned. In the end, however, the fat and skin passes ended up producing Chris' favourite results. The extra time spent perfecting the passes was significantly less than the time normally spent making corrective shapes and the results entirely exceeded Chris' expectations.

"When it comes to reproducing specialized elastics such as skin, Ziva shines and saves a ton of time. I enjoyed being able to spend my time working on the actual rig simulation rather than worrying about skin acting like skin.

Christopher Macwana, Lead Creature TD, Barajoun Entertainment

Christopher Macwana

Christopher Macwana is transforming the creature rigging department at Barajoun Entertainment, where he's works as a Lead Character TD. Chris has contributed to numerous blockbuster titles such as Dylan Dog: Dead Of Night, Disney’s Tinkerbell movies, and Hellboy (2018). His most notable creature work was completed on the Special Venue Ride show “Skull Island: Reign of Kong”, where he worked on assets such as King Kong, T-Rexes, and Velociraptors, ranging from 1500 to 4000 frames and 60 fps.

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The Anatomical Deer

Christopher Macwana, Lead Creature TD, Barajoun Entertainment
February 2, 2020
The Anatomical Deer was created by Barajoun Entertainment's Lead Creature TD and dedicated VFX artists, Christopher Macawna. With over 16 years of creature rigging experience, Macwana wanted to challenge his technical and creative capabilities by simulating his first anatomical, muscle-driven creature using Ziva VFX, from scratch. Chris chose the deer for their naturally thin skin and short fur which could highlight the intricate muscle system and its many subtle nuances.

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