Articulated tracking with manifold regularized particle filter-Reference-Cited by-同舟云学术

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Articulated tracking with manifold regularized particle filter

Published:2016-02 Issue:2 Volume:27 Page:275-286
ISSN:0932-8092
Container-title:Machine Vision and Applications
language:en
Short-container-title:Machine Vision and Applications

Author:

Gonczarek Adam,Tomczak Jakub M.

Funder

er EMinistry of Science and Highducation, Republic of Poland

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

http://link.springer.com/content/pdf/10.1007/s00138-016-0748-8.pdf

Reference29 articles.

1. Agarwal, A., Triggs, B.: Recovering 3d human pose from monocular images. Pattern Anal. Mach. Intell. IEEE Trans. 28(1), 44–58 (2006)

2. Andriluka, M., Roth, S., Schiele, B.: Monocular 3D pose estimation and tracking by detection. In: CVPR ’10 Proceedings of the 2010 IEEE Conference on Computer Vision and Pattern Recognition (2010)

3. Bo, L., Sminchisescu, C.: Twin Gaussian processes for structured prediction. Int. J. Comput. Vis. 87, 28–52 (2010)

4. Daubney, B., Gibson, D., Campbell, N.: Real-time pose estimation of articulated objects using low-level motion. In: CVPR ’08 Proceedings of the 2008 IEEE Conference on Computer Vision and Pattern Recognition (2008)

5. Daubney, B., Xie, X.: Tracking 3D human pose with large root node uncertainty. In: CVPR ’11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition (2011)

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4. Predictive Sampling of Facial Expression Dynamics Driven by a Latent Action Space;2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS);2018-11

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