The results of two experiments showed that the solution of the skeleton point solved the problem caused by data loss due to the Kinect optical occlusion.

Finally, using the least squares polynomial fitting to compensate and correct the lost skeleton coordinate data, it realizes the smoothness and rationality of human skeleton animation. Then, the dynamic acceleration of skeleton motion and the spatial characteristics of static limb motion were calculated based on the data of adjacent effective skeleton frames before and after the collision. Firstly, the constraint characteristics of human skeleton motion were analyzed, and the maximum constraint table and Mesh Collider were established. Based on the analysis of the spatial characteristics of gymnastics and the movement principle of the human body, this paper proposes a dynamic and static two-dimensional regression compensation algorithm. Most of the existing research focuses on local motion but lacks consideration of the whole human skeleton. It is necessary to reduce data noise via specific algorithms. However, its optical characteristics are inevitably affected by illumination and occlusion.

Microsoft Kinect has been widely used due to its advantages of low price and high frame rate. The intelligent training and assessment of gymnastics movements require studying motion trajectory and reconstructing the character animation.

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