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Anatomy Transfer

Ali-Hamadi Dicko, Tiantian Liu, Benjamin Gilles, Ladislav Kavan, Francois Faure, Olivier Palombi, Marie-Paule Cani

SIGGRAPH AsiaAcademic92 cites11 descendantsMuscles

Transfers a full anatomical model (bones, muscles, fat) onto arbitrary character shapes, automating anatomy-based rig setup.

Abstract

Characters with precise internal anatomy are important in film and visual effects, as well as in medical applications. We propose the first semi-automatic method for creating anatomical structures, such as bones, muscles, viscera and fat tissues. This is done by transferring a reference anatomical model from an input template to an arbitrary target character, only defined by its boundary representation (skin). The fat distribution of the target character needs to be specified. We can either infer this information from MRI data, or allow the users to express their creative intent through a new editing tool. The rest of our method runs automatically: it first transfers the bones to the target character, while maintaining their structure as much as possible. The bone layer, along with the target skin eroded using the fat thickness information, are then used to define a volume where we map the internal anatomy of the source model using harmonic (Laplacian) deformation. This way, we are able to quickly generate anatomical models for a large range of target characters, while maintaining anatomical constraints.

How to read this

Category
Method: anatomy transfer for rig setup
Contributions
  • First semi-automatic method to create internal anatomy (bones, muscles, viscera, fat) by transferring a reference model to a target defined only by its skin
  • Transfers bones while preserving their structure, then maps interior anatomy via harmonic (Laplacian) deformation into a volume bounded by skin and bone
  • Drives the target fat distribution either from MRI data or from an interactive editing tool for creative control
Context
Extends anatomically based character modeling (Teran et al. Creating and Simulating Skeletal Muscle from the Visible Human Data Set) by automating anatomy setup onto arbitrary target shapes.Builds on: Creating and Simulating Skeletal Muscle from the Visible Human Data Set
Correctness
Demonstrated across a range of target characters while maintaining anatomical constraints; it is semi-automatic (fat distribution must be supplied) and transfer quality depends on correspondence between the template and a target that differs strongly in proportion.
Clarity
Accessible pipeline; a first pass conveys the transfer stages, a second pass is needed for the harmonic mapping and constraint handling.
How to read it
Focus on the bone-then-interior transfer stages and the fat-distribution input; a second pass on the Laplacian volume mapping pays off if you intend to set up anatomy-based rigs.

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