The DOI matches its Crossref record.
Efficient generation of motion transitions using spacetime constraints
Open accessAbstract
This paper describes the application of space time constraints to creating transitions between segments of human body motion.The motion transition generation uses a combination of spacetime constraints and inverse kinematic constraints to generate seamless and dynamically plausible transitions between motion segments.We use a fast recursive dynamics formulation which makes it possible to use spacetime constraints on systems with many degrees of freedom, such as human figures.The system uses an interpreter of a motion expression language to allow the user to manipulate motion data, break it into pieces, and reassemble it into new, more complex, motions.We have successfully used the system to create basis motions, cyclic data, and seamless motion transitions on a human body model with 44 degrees of freedom.
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
Cited by
Synthesis and evaluation of linear motion transitions
Wang, J., & Bodenheimer, B. (2008) · ACM Transactions on Graphics · doi:10.1145/1330511.1330512 · Cited by 1,534
Self-citationKovar, L., Gleicher, M., & Pighin, F. (2008) · ACM SIGGRAPH 2008 classes · doi:10.1145/1401132.1401202 · Cited by 1,052
Retargetting motion to new characters
Gleicher, M. (1998) · Proceedings of the 25th annual conference on Computer graphics and interactive techniques - SIGGRAPH '98 · doi:10.1145/280814.280820 · Cited by 854
Motion editing with spacetime constraints
Gleicher, M. (1997) · Proceedings of the 1997 symposium on Interactive 3D graphics - SI3D '97 · doi:10.1145/253284.253321 · Cited by 293
Modeling the constraints of human hand motion
Lin, J., Wu, Y., & Huang, T. S. (2002) · Proceedings Workshop on Human Motion · doi:10.1109/humo.2000.897381 · Cited by 270
Metadata
- Authors
- Rose, C., Guenter, B., Bodenheimer, B., & Cohen, M. F.
- Venue
- Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
- Publisher
- ACM
- Published
- 1996-08
- Pages
- 147-154
- OpenAlex
- W1970552420
- Cited by
- 321
- References
- 0
- FWCI
- 33.92
- Type
- conference paper
- Language
- en
- Open access
- bronze
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: Efficient generation of motion transitions using spacetime constraints. https://app.cochat.ai/papers/10.1145/237170.237229
- The paper
- Rose, C., Guenter, B., Bodenheimer, B., & Cohen, M. F. (1996). Efficient generation of motion transitions using spacetime constraints. Proceedings of the 23rd annual conference on Computer graphics and interactive techniques. https://doi.org/10.1145/237170.237229
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.
