The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
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. In addition, image‐space techniques and stochastic methods are considered. Applications in cloth modeling and surgical simulation are presented.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A fast marching level set method for monotonically advancing fronts.
Sethian, J. A. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.4.1591 · Cited by 3,221
OBBTree: a hierarchical structure for rapid interference detection
Gottschalk, S., Lin, M. C., & Manocha, D. (1996) · Proceedings of the 23rd annual conference on Computer graphics and interactive techniques · doi:10.1145/237170.237244 · Cited by 2,081
Large steps in cloth simulation
Baraff, D., & Witkin, A. (1998) · Proceedings of the 25th annual conference on Computer graphics and interactive techniques - SIGGRAPH '98 · doi:10.1145/280814.280821 · Cited by 1,684
(2003) · Computer Graphics Forum · doi:10.1111/1467-8659.00652 · Cited by 1,436
Shade, J., Gortler, S., He, L.-W., & Szeliski, R. (1998) · Proceedings of the 25th annual conference on Computer graphics and interactive techniques - SIGGRAPH '98 · doi:10.1145/280814.280882 · Cited by 1,115
Efficient collision detection using bounding volume hierarchies of k-DOPs
Klosowski, J. T., Held, M., Mitchell, J. S. B., Sowizral, H., & Zikan, K. (1998) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/2945.675649 · Cited by 873
Pose space deformation: a unified approach to shape interpolation and skeleton-driven deformation
Lewis, J. P., Cordner, M., & Fong, N. (2000) · Proceedings of the 27th annual conference on Computer graphics and interactive techniques - SIGGRAPH '00 · doi:10.1145/344779.344862 · Cited by 853
Efficient Collision Detection of Complex Deformable Models using AABB Trees
Bergen, G. V. D. (1997) · Journal of Graphics Tools · doi:10.1080/10867651.1997.10487480 · Cited by 801
Robust treatment of collisions, contact and friction for cloth animation
Bridson, R., Fedkiw, R., & Anderson, J. (2002) · ACM Transactions on Graphics · doi:10.1145/566654.566623 · Cited by 618
Adaptively sampled distance fields: a general representation of shape for computer graphics
Frisken, S. F., Perry, R. N., Rockwood, A. P., & Jones, T. R. (2000) · Proceedings of the 27th annual conference on Computer graphics and interactive techniques - SIGGRAPH '00 · doi:10.1145/344779.344899 · Cited by 577
Cited by
Expressive Body Capture: 3D Hands, Face, and Body From a Single Image
Pavlakos, G., Choutas, V., Ghorbani, N., Bolkart, T., Osman, A. A., Tzionas, D., & Black, M. J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.01123 · Cited by 1,781
Physically Based Deformable Models in Computer Graphics
Nealen, A., Müller, M., Keiser, R., Boxerman, E., & Carlson, M. (2006) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2006.01000.x · Cited by 759
Metadata
- Authors
- Teschner, M., Kimmerle, S., Heidelberger, B., Zachmann, G., Raghupathi, L., Fuhrmann, A., Cani, M. ‐., Faure, F., Magnenat‐Thalmann, N., Strasser, W., & Volino, P.
- Venue
- Computer Graphics Forum
- Publisher
- Wiley
- Published
- 2005-03
- Volume
- 24
- Issue
- 1
- Pages
- 61-81
- ISSN
- 0167-7055 (ISSN-L)
- 1467-8659
- OpenAlex
- W2127794343
- Cited by
- 507
- References
- 54
- FWCI
- 69.38
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Collision Detection for Deformable Objects. https://app.cochat.ai/papers/10.1111/j.1467-8659.2005.00829.x
- The paper
- Teschner, M., Kimmerle, S., Heidelberger, B., Zachmann, G., Raghupathi, L., Fuhrmann, A., Cani, M. ‐., Faure, F., Magnenat‐Thalmann, N., Strasser, W., & Volino, P. (2005). Collision Detection for Deformable Objects. Computer Graphics Forum. https://doi.org/10.1111/j.1467-8659.2005.00829.x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.