Real-time upper-body human pose estimation from depth data using Kalman filter for simulator
Donghoon Lee, Suyoung Chi, C. Park, H.Y. Yoon, J. Kim, C. H. Park · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2014
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.