Sports movements modification based on ۲D joint position using YOLO to ۳D skeletal model adaptation

Doing sports movements correctly is very important in ensuring body health. In this article, an attempt has been made to achieve the movements correction through the usage of a different approach based on the ۲D position of the joints from the image in ۳D space. A person performing in front of the camera with landmarks on his/her joints is the subject of the input image. The coordinates of the joints are then measured in ۲D space which is adapted to the extracted ۲D skeletons from the reference skeletal sparse model modified movements. The accuracy and precision of this approach is accomplished on the standard Adidas dataset. Its efficiency has also been studied under the influence of cumulative Gaussian and impulse noises. Meanwhile, the average error of the model in detecting the wrong exercise in the set of sports movements is reported to be ۵.۶۹ pixels.

کلیدواژه ها:

Sports movements ، Yolo neural network ، sparse model