Three-Dimensional Action Recognition for Basketball Teaching Coupled with Deep Neural Network
نویسندگان
چکیده
This study proposes a 3D attitude estimation algorithm using the RMPE coupled with deep neural network that combines human pose and action recognition, which provides new idea for basketball auxiliary training. Compared traditional single-action recognition method, present method makes accuracy better display effect more intuitive. The flipped classroom teaching mode based on this is applied to college sports optional course explore influence of effect. evaluation index experimental results various methods datasets are compared analyzed, it verified has good values Topi Top5 proposed 42.21% 88.77%, respectively, 10.61% 35.09% higher than those Kinetics-skeleton dataset. However, NTU RGM dataset, rate significantly reduced. intuitive fusion posture motion
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ژورنال
عنوان ژورنال: Electronics
سال: 2022
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics11223797