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Conference Paper Real-time Upper-body Human Pose Estimation from Depth Data using Kalman Filter for Simulator
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Authors
D. Lee, S. Chi, C. Park, H. Yoon, J. Kim, C. H. Park
Issue Date
2014-05
Citation
International Conference on Applications of Optics and Photonics 2014, pp.1-9
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1117/12.2064621
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.
KSP Keywords
Back pain, Depth Data, Depth image, Ground truth data, Horse Riding, Human pose estimation, Joint Estimation, Real-Time, estimation algorithm, kalman filter