Sports movements modification based on 2D joint position using YOLO to 3D skeletal model adaptation

Doing sports movements correctly is very important in ensuring body health. In this work, an attempt is made to achieve the movements correction through the usage of a different approach based on the 2D position of the joints from the image in 3D 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 2D space which is adapted to the extracted 2D skeletons from the reference skeletal sparse model modified movements. The accuracy and precision of this approach are accomplished on the standard Adidas dataset. Its efficiency is also 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 5.69 pixels.