MTS 2024, Article 36 (pp. 1 to 8)
[ACTIVE]
The Advance of Markerless Motion Capture Technology and Its Impact on Animation
Metadata
- Publisher
- SMPTE — Hollywood, CA
- Doc Type
- Conference Paper
- Content Type
- Original Research
- Volume
- 00, pp. 1–8
- Abstract
- The motion capture industry has enabled animators to produce realistic and high-quality animations but is still plagued by the need for expensive equipment. Much research has been done to provide accessible and efficient motion capture technologies, as well as develop methods to improve animator efficiency. Advancements in the medical industry have inspired motion capture technologies as kinesiologists are looking for effective ways to better analyze kinematics in the human body. A common goal for a kinesiologist is to obtain a fine-grained understanding of an athlete's motion as well the physics of how their joints are moving to provide feedback towards peak athlete performance. Towards this goal, a fully automated system was developed that takes input videos from an agnostic set of cameras to create a 3D kinematic model unique to the actor and their motion. This originating technology is being transitioned to be usable by the animation industry. During this transition, new features are in development including speeding up processing time and building compatibility for common animation software. The work presented herein describes the challenges, strategy, and impact expected during the transition of a biomechanic inspired motion capture system to the animation industry.
- Publication Date
- 2024-10-21
- DOI
10.5594/MOO/3047- ISBN
- Electronic:
978-1-61482-965-2 - Link
- https://doi.org/10.5594/MOO/3047
- Author(s)
- Jonathan Esquivel
- Keyword(s)
- Artificial Intelligence, Computer Vision, Motion Capture, Animation, Sports Science
- Copyright
- © 2024 SMPTE
Bibliographic Reference(s)
- Andriluka, M., Pishchulin, L., Gehler, P., & Schiele, B. (2014, 23–28 June 2014). 2D Human Pose Estimation: New Benchmark and State of the Art Analysis. 2014 IEEE Conference on Computer Vision and Pattern Recognition. EXTERNAL
- Johnson, S., & Everingham, M. (2010). Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation. British Machine Vision Conference. EXTERNAL
- Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014). Microsoft COCO: Common Objects in Context. In (pp. 740–755). Springer International Publishing. https://doi.org/10.1007/978-3-319-10602-1_48. EXTERNAL
- Song, K., Hullfish, T. J., Scattone Silva, R., Silbernagel, K. G., & Baxter, J. R. (2023). Markerless motion capture estimates of lower extremity kinematics and kinetics are comparable to marker-based across 8 movements. Journal of Biomechanics, 157, 111751. https://doi.org/10.1016/j.jbiomech.2023.111751 EXTERNAL
- Weitz, A., Colucci, L., Primas, S., & Bent, B. (2021). InfiniteForm: A synthetic, minimal bias dataset for fitness applications. arXiv:2110.01330. EXTERNAL
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Jonathan Esquivel; The Advance of Markerless Motion Capture Technology and Its Impact on Animation, MTS 2024, Article 36 (pp. 1 to 8); SMPTE, 2024, ISBN: 978-1-61482-965-2. Available at https://doi.org/10.5594/MOO/3047
Snippet:
Jonathan Esquivel; The Advance of Markerless Motion Capture Technology and Its Impact on Animation, MTS 2024, Article 36 (pp. 1 to 8); SMPTE, 2024, ISBN: 978-1-61482-965-2. Available at https://doi.org/10.5594/MOO/3047
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Jonathan Esquivel; The Advance of Markerless Motion Capture Technology and Its Impact on Animation, MTS 2024, Article 36 (pp. 1 to 8); SMPTE, 2024, ISBN: 978-1-61482-965-2. Available at https://doi.org/10.5594/MOO/3047
Snippet:
<span class="citation">Jonathan Esquivel; <cite>The Advance of Markerless Motion Capture Technology and Its Impact on Animation</cite>, MTS 2024, Article 36 (pp. 1 to 8); SMPTE, 2024, ISBN: 978-1-61482-965-2. Available at <a href="https://doi.org/10.5594/MOO/3047" target="_blank" rel="noopener">https://doi.org/10.5594/MOO/3047</a></span>
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Jonathan Esquivel; The Advance of Markerless Motion Capture Technology and Its Impact on Animation, MTS 2024, Article 36 (pp. 1 to 8); SMPTE, 2024, ISBN: 978-1-61482-965-2
doi: 10.5594/MOO/3047
url: https://doi.org/10.5594/MOO/3047
doi: 10.5594/MOO/3047
url: https://doi.org/10.5594/MOO/3047
Snippet:
<li> Jonathan Esquivel; <cite id="bib-10-5594-moo-3047">The Advance of Markerless Motion Capture Technology and Its Impact on Animation</cite>, MTS 2024, Article 36 (pp. 1 to 8); SMPTE, 2024, ISBN: 978-1-61482-965-2 <span class="doi">10.5594/MOO/3047</span> </li>