The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Model-based 3D tracking of an articulated hand
Abstract
This paper presents a practical technique for model-based 3D hand tracking. An anatomically accurate hand model is built from truncated quadrics. This allows for the generation of 2D profiles of the model using elegant tools from projective geometry, and for an efficient method to handle self-occlusion. The pose of the hand model is estimated with an Unscented Kalman filter (UKF), which minimizes the geometric error between the profiles and edges extracted from the images. The use of the UKF permits higher frame rates than more sophisticated estimation methods such as particle filtering, whilst providing higher accuracy than the extended Kalman filter The system is easily scalable from single to multiple views, and from rigid to articulated models. First experiments on real data using one and two cameras demonstrate the quality of the proposed method for tracking a 7 DOF hand model.
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Citations
Cites
CONDENSATION—Conditional Density Propagation for Visual Tracking
Isard, M., & Blake, A. (1998) · International Journal of Computer Vision · doi:10.1023/a:1008078328650 · Cited by 4,886
Cited by
Romero (2017) · doi:10.1145/3130800.3130883 · Cited by 1,056
Efficient model-based 3D tracking of hand articulations using Kinect
Oikonomidis, I., Kyriazis, N., & Argyros, A. (2011) · Procedings of the British Machine Vision Conference 2011 · doi:10.5244/c.25.101 · Cited by 874
Learning Joint Reconstruction of Hands and Manipulated Objects
Hasson, Y., Varol, G., Tzionas, D., Kalevatykh, I., Black, M. J., Laptev, I., & Schmid, C. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.01208 · Cited by 513
Accurate, Robust, and Flexible Real-time Hand Tracking
Sharp, T., Keskin, C., Robertson, D., Taylor, J., Shotton, J., Kim, D., Rhemann, C., Leichter, I., Vinnikov, A., Wei, Y., et al. (2015) · Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702179 · Cited by 431
Vision Based Hand Gesture Recognition
Garg, P., Aggarwal, N., & Sofat, S. (2009) · doi:10.5281/zenodo.1074854 · Cited by 275
Metadata
- Authors
- Stenger, B., Mendonca, P. R. S., & Cipolla, R.
- Venue
- Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001
- Publisher
- IEEE Comput. Soc
- Published
- 2005-08-24
- Volume
- 2
- Pages
- II-310-II-315
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2166665167
- Cited by
- 263
- References
- 1
- FWCI
- 15.14
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Stenger, B., Mendonca, P. R. S., & Cipolla, R. (2005). Model-based 3D tracking of an articulated hand. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001. https://doi.org/10.1109/cvpr.2001.990976
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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.
