The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Motion capture using joint skeleton tracking and surface estimation
Abstract
This paper proposes a method for capturing the performance of a human or an animal from a multi-view video sequence. Given an articulated template model and silhouettes from a multi-view image sequence, our approach recovers not only the movement of the skeleton, but also the possibly non-rigid temporal deformation of the 3D surface. While large scale deformations or fast movements are captured by the skeleton pose and approximate surface skinning, true small scale deformations or non-rigid garment motion are captured by fitting the surface to the silhouette. We further propose a novel optimization scheme for skeleton-based pose estimation that exploits the skeleton's tree structure to split the optimization problem into a local one and a lower dimensional global one. We show on various sequences that our approach can capture the 3D motion of animals and humans accurately even in the case of rapid movements and wide apparel like skirts.
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Citations
Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
A survey of advances in vision-based human motion capture and analysis
Moeslund, T. B., Hilton, A., & Krüger, V. (2006) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2006.08.002 · Cited by 2,541
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
SCAPE: shape completion and animation of people
Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., & Davis, J. (2005) · ACM Transactions on Graphics · doi:10.1145/1073204.1073207 · Cited by 1,489
Sigal, L., Balan, A. O., & Black, M. J. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-009-0273-6 · Cited by 1,164
3-D model-based tracking of humans in action: a multi-view approach
Gavrila, D. M., & Davis, L. S. (1996) · Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1996.517056 · Cited by 702
Articulated mesh animation from multi-view silhouettes
Vlasic, D., Baran, I., Matusik, W., & Popović, J. (2008) · ACM Transactions on Graphics · doi:10.1145/1360612.1360696 · Cited by 610
On Linear Variational Surface Deformation Methods
Botsch, M., & Sorkine, O. (2008) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2007.1054 · Cited by 582
Performance capture from sparse multi-view video
de Aguiar, E., Stoll, C., Theobalt, C., Ahmed, N., Seidel, H.-P., & Thrun, S. (2008) · ACM Transactions on Graphics · doi:10.1145/1360612.1360697 · Cited by 535
Self-citationAutomatic rigging and animation of 3D characters
Baran, I., & Popović, J. (2007) · ACM SIGGRAPH 2007 papers · doi:10.1145/1275808.1276467 · Cited by 495 · cited 1×
“Thereafter, weights ρ i,k are automatically computed for each V i which describe the association of V i with each bone k [5].”
Method
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
A Survey on Shape Correspondence
van Kaick, O., Zhang, H., Hamarneh, G., & Cohen‐Or, D. (2011) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2011.01884.x · Cited by 606
High-quality streamable free-viewpoint video
Collet, A., Chuang, M., Sweeney, P., Gillett, D., Evseev, D., Calabrese, D., Hoppe, H., Kirk, A., & Sullivan, S. (2015) · ACM Transactions on Graphics · doi:10.1145/2766945 · Cited by 573
Survey on Emotional Body Gesture Recognition
Noroozi, F., Corneanu, C. A., Kaminska, D., Sapinski, T., Escalera, S., & Anbarjafari, G. (2021) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2018.2874986 · Cited by 455
Function4D: Real-time Human Volumetric Capture from Very Sparse Consumer RGBD Sensors
Yu, T., Zheng, Z., Guo, K., Liu, P., Dai, Q., & Liu, Y. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00569 · Cited by 355
Metadata
- Authors
- Gall, J., Stoll, C., de Aguiar, E., Theobalt, C., Rosenhahn, B., & Seidel, H.-P.
- Venue
- 2009 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2009-06
- Pages
- 1746-1753
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2110434318
- Cited by
- 344
- References
- 28
- FWCI
- 17.17
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Gall, J., Stoll, C., de Aguiar, E., Theobalt, C., Rosenhahn, B., & Seidel, H.-P. (2009). Motion capture using joint skeleton tracking and surface estimation. 2009 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2009.5206755
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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).
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