The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Dynamics based 3D skeletal hand tracking
Open accessAbstract
Natural human computer interaction motivates hand tracking research, preferably without requiring the user to wear special hardware or markers. Ideally, a hand tracking solution would provide not only points of interest, but the full state of an entire hand. [Oikonomidis et al. 2011] demonstrated a particle swarm optimization that tracked a 3D skeletal hand model from a single depth camera, albeit using significant computing resources. In contrast, we track the hand from a single depth camera using an efficient physical simulation, which incrementally updates a model's fit and explores alternative candidate poses based on a variety of heuristics. Our approach enables real-time, robust 3D skeletal tracking of a user's hand, while utilizing a single x86 CPU core for processing.
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Cites
An efficient k-means clustering algorithm: analysis and implementation
Kanungo, T., Mount, D. M., Netanyahu, N. S., Piatko, C. D., Silverman, R., & Wu, A. Y. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017616 · Cited by 5,660
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
Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking
Cao, J., Pang, J., Weng, X., Khirodkar, R., & Kitani, K. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52729.2023.00934 · Cited by 1,115
Romero (2017) · doi:10.1145/3130800.3130883 · Cited by 1,056
Intel(R) RealSense(TM) Stereoscopic Depth Cameras
Keselman, L., Woodfill, J. I., Grunnet-Jepsen, A., & Bhowmik, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2017.167 · Cited by 448
Self-citationAccurate, 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
Metadata
- Authors
- Melax, S., Keselman, L., & Orsten, S.
- Venue
- Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
- Publisher
- ACM
- Published
- 2013-03-21
- Pages
- 184-184
- OpenAlex
- W1633557510
- Cited by
- 172
- References
- 1
- FWCI
- 15.28
- Type
- conference paper
- Language
- en
- Open access
- green
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- Melax, S., Keselman, L., & Orsten, S. (2013). Dynamics based 3D skeletal hand tracking. Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games. https://doi.org/10.1145/2448196.2448232
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