← ArchivePaper2014
A Reduced Model for Interactive Hairs
Guide-strand reduced model with optimal interpolation relationships simulates 150K hair strands in real time with a hair-correction collision pass.
Abstract
Realistic hair animation is a crucial component in depicting virtual characters in interactive applications. While much progress has been made in high-quality hair simulation, the overwhelming computation cost hinders similar fidelity in realtime simulations. To bridge this gap, we propose a data-driven solution. Building upon precomputed simulation data, our approach constructs a reduced model to optimally represent hair motion characteristics with a small number of guide hairs and the corresponding interpolation relationships. At runtime, utilizing such a reduced model, we only simulate guide hairs that capture the general hair motion and interpolate all rest strands. We further propose a hair correction method that corrects the resulting hair motion with a position-based model to resolve hair collisions and thus captures motion details. Our hair simulation method enables a simulation of a full head of hairs with over 150K strands in realtime. We demonstrate the efficacy and robustness of our method with various hairstyles and driven motions (e.g., head movement and wind force), and compared against full simulation results that does not appear in the training data.
How to read this
- Category
- Method: data-driven reduced model for real-time hair simulation
- Contributions
- A reduced model, built from precomputed simulation data, that represents hair motion with a small number of guide hairs plus optimal interpolation relationships
- A runtime scheme simulating only guide hairs and interpolating the rest, reaching real-time simulation of full heads with over 150K strands
- A position-based hair correction pass that resolves collisions and recovers motion detail
- Context
- A data-driven reduction over full hair simulation, building on mass-spring hair dynamics such as Selle et al.'s A Mass Spring Model for Hair Simulation.Builds on: A Mass Spring Model for Hair Simulation
- Correctness
- Assumes guide hairs plus learned interpolation capture general motion and that the correction pass handles collisions; quality depends on the precomputed training set, and the authors note comparison against full simulations including motions not in the training data, which is the key generalization concern.
- Clarity
- Accessible; a first pass conveys the guide-hair plus interpolation plus correction structure, a second pass clarifies how interpolation relationships are learned.
- How to read it
- Focus on how guide hairs and interpolation weights are chosen and what the correction pass adds; a second pass pays off for the reduced-model construction and out-of-training behavior.
Builds on
Built upon by
Related work
- Physics-Inspired Upsampling for Cloth Simulation in Games 2021 / SIGGRAPH
- Artistic Simulation of Curly Hair 2013 / SCA
- Fast Automatic Skinning Transformations 2012 / SIGGRAPH
- Hair Modeling and Simulation by Style 2018 / CGF
Keywords
This page summarises the entry and links to its original source. The archive never hosts or redistributes the publication itself.Show it in the full archive list →