Optical Flow Based Pose Estimation-Reference-Cited by-同舟云学术

Optical Flow Based Pose Estimation

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 2nd International Conference on Cloud and Big Data Computing - ICCBDC'18
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Author:

Alper Mehmet Akif¹,Al-Ghezi Hammid²,Nassib Ali²,Guzel Yasar²

Affiliation:

1. Michigan State University, Lansing, MI, USA

2. University of Dayton, Dayton, OH, USA

Publisher

ACM Press

Reference8 articles.

1. U. Asif, M. Bennamoun, and F. Sohel. Real-time pose estimation of rigid objects using RGB-d imagery. In IEEE Conference on Industrial Electronics and Applications (Melbourne, Australia, 2013). IEEE, 692--1699.

2. M. Zia, M. Stark, B. Schiele, and K. Schindler. Revisiting 3d geometric models for accurate object shape and pose. In IEEE International Conference on Computer Vision (Barcelona, Spain, 2011). IEEE, 569--576.

3. Z. Yun-feng, S. Gan-lin, and J. Bing. A dynamic-template-library based method to measure the pose of maneuvering target. In IEEE Conference on Industrial Electronics and Applications (Xi'an, China). IEEE, 2080--2084.

4. D. Boscaini, J. Masci, E. Rodola, M. M. Bronstein, and D. Cremers. Anisotropic diffusion descriptors. In Proceeding of the 37th Annual Conference of the European Association for Computer Graphics (Lisbon, Portugal, 2016). Eurographics Association Aire-la-Ville, Switzerland, 431--441.

5. S. Bouaziz, Y. Wang, and M. Pauly. Online modeling for realtime facial animation. ACM Transactions on Graphics. 32, 4 (July 2013). ACM, New York, NY, 40.

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