Skip to Main content Skip to Navigation
Conference papers

Collision Detection for Deformable Objects

Abstract : Interactive environments for dynamically deforming objects play an important role in surgery simulation and entertainment technology. These environments require fast deformable models and very efficient collision handling techniques. While collision detection for rigid bodies is well-investigated, collision detection for deformable objects introduces additional challenging problems. This paper focuses on these aspects and summarizes recent research in the area of deformable collision detection. Various approaches based on bounding volume hierarchies, distance fields, and spatial partitioning are discussed. Further, image-space techniques and stochastic methods are considered. Applications in cloth modeling and surgical simulation are presented.
Document type :
Conference papers
Complete list of metadata

Cited literature [72 references]  Display  Hide  Download


https://hal.inria.fr/inria-00539916
Contributor : Team Artis Connect in order to contact the contributor
Submitted on : Thursday, November 25, 2010 - 3:17:04 PM
Last modification on : Thursday, May 27, 2021 - 1:54:05 PM
Long-term archiving on: : Saturday, February 26, 2011 - 3:00:28 AM

Files

STARmain.pdf
Publisher files allowed on an open archive

Identifiers

  • HAL Id : inria-00539916, version 1

Collections

IMAG | CNRS | INRIA | UGA

Citation

Matthias Teschner, Stefan Kimmerle, Bruno Heidelberger, Gabriel Zachmann, Laks Raghupathi, et al.. Collision Detection for Deformable Objects. Eurographics State-of-the-Art Report (EG-STAR), Aug 2004, Grenoble, France. ⟨inria-00539916⟩

Share

Metrics

Record views

2246

Files downloads

5103