The DOI matches its Crossref record.
Cardboard people: a parameterized model of articulated image motion
Abstract
We extend the work of Black and Yacoob (1995) on the tracking and recognition of human facial expressions using parametrized models of optical flow to deal with the articulated motion of human limbs. We define a "card-board person model" in which a person's limbs are represented by a set of connected planar patches. The parametrized image motion of these patches in constrained to enforce articulated motion and is solved for directly using a robust estimation technique. The recovered motion parameters provide a rich and concise description of the activity that can be used for recognition. We propose a method for performing view-based recognition of human activities from the optical flow parameters that extends previous methods to cope with the cyclical nature of human motion. We illustrate the method with examples of tracking human legs of long image sequences.
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
W/sup 4/: real-time surveillance of people and their activities
Haritaoglu, I., Harwood, D., & Davis, L. S. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.868683 · Cited by 2,523
Human motion tracking for rehabilitation-A survey
Zhou, H., & Hu, H. (2008) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2007.09.001 · Cited by 813
Duric, Z., Gray, W. D., Heishman, R., Li, F., Rosenfeld, A., Schoelles, M. J., Schunn, C., & Wechsler, H. (2002) · Proceedings of the IEEE · doi:10.1109/jproc.2002.801449 · Cited by 185
Metadata
- Authors
- Ju, S. X., Black, M. J., & Yacoob, Y.
- Venue
- Proceedings of the Second International Conference on Automatic Face and Gesture Recognition
- Publisher
- IEEE Comput. Soc. Press
- Published
- 2002-12-23
- Pages
- 38-44
- ISSN
- 1541-5058 (ISSN-L)
- OpenAlex
- W2133716807
- Cited by
- 436
- References
- 0
- FWCI
- 26.75
- Type
- conference paper
- 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: Cardboard people: a parameterized model of articulated image motion. https://app.cochat.ai/papers/10.1109/afgr.1996.557241
- The paper
- Ju, S. X., Black, M. J., & Yacoob, Y. (2002). Cardboard people: a parameterized model of articulated image motion. Proceedings of the Second International Conference on Automatic Face and Gesture Recognition. https://doi.org/10.1109/afgr.1996.557241
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.
