1 - Zhejiang University, China

2 - University of North Carolina at Chapel Hill, USA

*Tongtong Wang and Zhihua Liu are joint first authors. Min Tang is the corresponding author.

Benchmarks: We use seven challenging benchmarks arising from deformable and cloth simulations. We compare the performance of our DCD and CCD algorithms with prior methods.

Abstract

We present an efficient and accurate algorithm for self-collision detection in deformable models. Our approach can perform discrete and continuous collision queries on triangulated meshes. We present a simple and linear time algorithm to perform the normal cone test using the unprojected 3D vertices, which reduces to a sequence point-plane classification tests. Moreover, we present a hierarchical traversal scheme that can significantly reduce the number of normal cone tests and the memory overhead using front-based normal cone culling. The overall algorithm can reliably detect all (self) collisions in models composed of hundred of thousands of triangles. We observe considerable performance improvement over prior CCD algorithms.
 

Contents

Related Links

I-Cloth: Incremental Collision Handling for GPU-Based Interactive Cloth Simulation

PSCC: Parallel Self-Collision Culling with Spatial Hashing on GPUs

I-Cloth: API for fast and reliable cloth simulation with CUDA

Efficient BVH-based Collision Detection Scheme with Ordering and Restructuring

MCCD: Multi-Core Collision Detection between Deformable Models using Front-Based Decomposition

Interactive Continuous Collision Detection between Deformable Models using Connectivity-Based Culling

TightCCD: Efficient and Robust Continuous Collision Detection using Tight Error Bounds

Fast and Exact Continuous Collision Detection with Bernstein Sign Classification

A GPU-based Streaming Algorithm for High-Resolution Cloth Simulation

Continuous Penalty Forces

UNC dynamic model benchmark repository

Collision-Streams: Fast GPU-based Collision Detection for Deformable Models

Fast Continuous Collision Detection using Deforming Non-Penetration Filters

Fast Collision Detection for Deformable Models using Representative-Triangles

DeformCD: Collision Detection between Deforming Objects

Self-CCD: Continuous Collision Detection for Deforming Objects

Interactive Collision Detection between Deformable Models using Chromatic Decomposition

Fast Proximity Computation Among Deformable Models using Discrete Voronoi Diagrams

CULLIDE: Interactive Collision Detection between Complex Models using Graphics Hardware

RCULLIDE: Fast and Reliable Collision Culling using Graphics Processors

Quick-CULLIDE: Efficient Inter- and Intra-Object Collision Culling using Graphics Hardware

Collision Detection

UNC GAMMA Group

UNC GAMMA Group

Acknowledgements

This research is supported in part by NSFC (61572423, 61572424), Zhejiang Provincial NSFC (LZ16F020003), and the Doctoral Fund of Ministry of Education of China (20130101110133).

CB #3175, Department of Computer Science
University of North Carolina
Chapel Hill, NC 27599-3175
919.962.1749
geom@cs.unc.edu