A data fusion-based method for detecting difficult yoga postures

Kaiyue Wang

doi:10.1117/12.2674850

23 May 2023 A data fusion-based method for detecting difficult yoga postures

Kaiyue Wang

Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 126041F (2023) https://doi.org/10.1117/12.2674850
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China

Abstract

The current traditional human pose detection methods mainly acquire the pose data collected by sensors and realize the pose discrimination by edge computing decision unit, which leads to poor detection effect due to the lack of fusion of sensor data. In this regard, a high difficulty yoga body pose detection method based on data fusion is proposed. Complementary filtering, Kalman filtering and adaptive Kalman filtering methods are used to fuse sensor data for pose prediction, and a skeleton extraction model is constructed to build a multilayer perceptron network architecture to achieve the detection of difficult yoga asana poses. In the experiments, the proposed human posture detection method is validated. The analysis of the experimental results shows that the proposed method has a high comprehensive evaluation index and excellent detection performance when used for the detection of difficult yoga asana postures.

Citation Download Citation

Kaiyue Wang "A data fusion-based method for detecting difficult yoga postures", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 126041F (23 May 2023); https://doi.org/10.1117/12.2674850

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