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Proceedings Paper

Real-time upper-body human pose estimation from depth data using Kalman filter for simulator
Author(s): D. Lee; S. Chi; C. Park; H. Yoon; J. Kim; C. H. Park
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Paper Abstract

Recently, many studies show that an indoor horse riding exercise has a positive effect on promoting health and diet. However, if a rider has an incorrect posture, it will be the cause of back pain. In spite of this problem, there is only few research on analyzing rider’s posture. Therefore, the purpose of this study is to estimate a rider pose from a depth image using the Asus’s Xtion sensor in real time. In the experiments, we show the performance of our pose estimation algorithm in order to comparing the results between our joint estimation algorithm and ground truth data.

Paper Details

Date Published: 22 August 2014
PDF: 9 pages
Proc. SPIE 9286, Second International Conference on Applications of Optics and Photonics, 928625 (22 August 2014); doi: 10.1117/12.2064621
Show Author Affiliations
D. Lee, Electronics and Telecommunications Research Institute (Korea, Republic of)
S. Chi, Electronics and Telecommunications Research Institute (Korea, Republic of)
C. Park, Electronics and Telecommunications Research Institute (Korea, Republic of)
H. Yoon, Electronics and Telecommunications Research Institute (Korea, Republic of)
J. Kim, Electronics and Telecommunications Research Institute (Korea, Republic of)
C. H. Park, Chungnam National Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 9286:
Second International Conference on Applications of Optics and Photonics
Manuel Filipe P. C. Martins Costa; Rogério Nunes Nogueira, Editor(s)

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