Sports movements modification based on 2D joint position using YOLO to 3D skeletal model adaptation | ||
| Journal of AI and Data Mining | ||
| دوره 10، شماره 4، بهمن 2022، صفحه 549-557 اصل مقاله (1.45 M) | ||
| نوع مقاله: Original/Review Paper | ||
| شناسه دیجیتال (DOI): 10.22044/jadm.2022.11975.2344 | ||
| نویسندگان | ||
| A. Rahati؛ K. Rahbar* | ||
| Department of Computer Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran. | ||
| چکیده | ||
| 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 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 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 5.69 pixels. | ||
| کلیدواژهها | ||
| Sports movements؛ Yolo neural network؛ sparse model | ||
| مراجع | ||
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