Technical Papers

Hair & Collisions

Wednesday, 13 August 3:45 PM - 5:15 PM | Vancouver Convention Centre, East Building, Ballroom A Session Chair: Sylvain Paris, Adobe, Adobe Systems Incorporated

Defending Continuous Collision Detection Against Errors

This paper presents a set of simple modifications to make the basic continuous collision-detection implementation failure-proof. Using error analysis, the paper proves the safety of this method and formulates suggested tolerance values to reduce false positives. The resulting algorithms are safe, automatic, efficient, and easy to implement.

Huamin Wang
The Ohio State University

Adaptive Nonlinearity for Collisions in Complex Rod Assemblies

This paper exposes and analyzes the strongly nonlinear behavior of thin-body collision response. To address this nonlinearity, the method develops a simple, adaptively nonlinear time-stepping algorithm to incorporate sufficient nonlinearity in collision-response modeling. This enables stable simulations at timesteps several orders of magnitude larger than previously possible.

Breannan Smith
Columbia University

Danny Kaufman
Adobe Systems Incorporated

Rasmus Tamstorf
Walt Disney Animation Studios

Eitan Grinspun
Columbia University

Jean-Marie Aubry
Weta Digital

A Reduced Model for Interactive Hairs

A real-time hair simulation method, using a data-driven reduced model, that simulates a few guide hairs and interpolates all other hairs using a skinning model. The paper also proposes a run-time hair correction method to recover hair motion details, which were previously captured only from full simulations.

Menglei Chai
Zhejiang University

Changxi Zheng
Columbia University

Kun Zhou
Zhejiang University

Capturing and Stylizing Hair for 3D Fabrication

The first method for *stylized* hair capture, a technique to reconstruct an individual's actual hairstyle in a manner suitable for physical reproduction.

Jose Ignacio Echevarria
Universidad de Zaragoza

Derek Bradley
Disney Research Zürich

Diego Gutierrez
Universidad de Zaragoza

Thabo Beeler
Disney Research Zürich

Robust Hair Capture Using Simulated Examples

Introducing a data-driven hair-capture framework based on example strands generated through hair simulation. The method is structurally plausible by construction and ensures improved control during hair digitization, avoiding implausible hair synthesis for a wide range of hairstyles.

Liwen Hu
University of Southern California

Chongyang Ma
University of Southern California

Linjie Luo
Adobe Research

Hao Li
University of Southern California