JACIII Vol.26 No.5 pp. 801-807
doi: 10.20965/jaciii.2022.p0801


Characteristic Behavior of Human Multi-Joint Spatial Trajectory in Slalom Skiing

Peizhang Li, Qing Fei, Zhen Chen, Xiaolan Yao, and Yijia Zhang

School of Automation, Beijing Institute of Technology
No.5 Zhong Guan Cun South Street, Haidian District, Beijing 100081, China

Corresponding author

March 15, 2022
June 27, 2022
September 20, 2022
slalom skiing, spatial trajectory, group characteristic, characteristic recognition

The scientific analysis of the slalom training process can significantly improve the performance of athletes. In this paper, the P matrix is defined by extracting the multi-joint space coordinate trajectories of the athletes in the video to analyze the slalom training pattern. The principal component analysis was used to extract the main eigenvalues and eigenvectors of the P matrix, which were defined as the main eigenbehaviors of slalom skiing, and six main eigenbehaviors were used to achieve a similarity of 96% between the reconstructed skiing sequence and the original sequence. Similarly, the group characteristic S matrix is constructed by using the individual eigenbehaviors, and the eigenvectors of the matrix are used to define the characteristic behavior of the group to classify the hierarchical group and determine the group to which the individual belongs. Results show that this method can better identify the movement pattern of the human body’s multi-joint space trajectory in indoor or outdoor slalom skiing, and provide scientific guidance for skiing training, so that athletes can achieve better training effectiveness.

Main eigenbehaviors of slalom skiing

Main eigenbehaviors of slalom skiing

Cite this article as:
P. Li, Q. Fei, Z. Chen, X. Yao, and Y. Zhang, “Characteristic Behavior of Human Multi-Joint Spatial Trajectory in Slalom Skiing,” J. Adv. Comput. Intell. Intell. Inform., Vol.26 No.5, pp. 801-807, 2022.
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