The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Tracking people with twists and exponential maps
Abstract
This paper demonstrates a new visual motion estimation technique that is able to recover high degree-of-freedom articulated human body configurations in complex video sequences. We introduce the use of a novel mathematical technique, the product of exponential maps and twist motions, and its integration into a differential motion estimation. This results in solving simple linear systems, and enables us to recover robustly the kinematic degrees-of-freedom in noise and complex self occluded configurations. We demonstrate this on several image sequences of people doing articulated full body movements, and visualize the results in re-animating an artificial 3D human model. We are also able to recover and re-animate the famous movements of Eadweard Muybridge's motion studies from the last century. To the best of our knowledge, this is the first computer vision based system that is able to process such challenging footage and recover complex motions with such high accuracy.
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Cites
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
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
A Survey of Computer Vision-Based Human Motion Capture
Moeslund, T. B., & Granum, E. (2001) · Computer Vision and Image Understanding · doi:10.1006/cviu.2000.0897 · Cited by 1,768
Gait analysis for recognition and classification
Lee, L., & Grimson, W. E. L. (2003) · Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition · doi:10.1109/afgr.2002.1004148 · Cited by 734
Real-time visual tracking of complex structures
Drummond, T., & Cipolla, R. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017620 · Cited by 598
Huang, Y., Kaufmann, M., Aksan, E., Black, M. J., Hilliges, O., & Pons-Moll, G. (2018) · ACM Transactions on Graphics · doi:10.1145/3272127.3275108 · Cited by 342
Metadata
- Authors
- Bregler, C., & Malik, J.
- Venue
- Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231)
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-27
- Pages
- 8-15
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2118025528
- Cited by
- 719
- References
- 1
- FWCI
- 54.09
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Bregler, C., & Malik, J. (2002). Tracking people with twists and exponential maps. Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231). https://doi.org/10.1109/cvpr.1998.698581
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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.
