Method for Extracting Data During Flight Phase of Ski Jumping Based on Monocular Video

Authors

Ziyi Shen, School of Information Science and Technology, Beijing Forestry University, Beijing 100083, ChinaFollow
Meng Yang, School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China; Engineering Research Center for Forestry-Oriented Intelligent Information Processing of National Forestry and Grassland Administration, Beijing 100083, ChinaFollow
Chao Yang, School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
Weidi Tang, Shanghai Institute of Physical Education, Shanghai 200438, China
Xie Wu, Shanghai Institute of Physical Education, Shanghai 200438, China
Yu Liu, Shanghai Institute of Physical Education, Shanghai 200438, China
Bin Sheng, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Abstract

Abstract: To solve the problem of the high difficulty factor of ski jumping and the difficulty of extracting data of this sport due to the danger of invasive devices such as wearable sensors and high price, a method for extracting data during the flight phase of ski jumping based on monocular video is proposed. The distortion and background clutter of the monocular video are preprocessed. The distortion of the captured images is corrected by calibrating camera parameters, and the background is removed by the inter-frame difference method. The human pose recognition library, namely OpenPose is used to initially identify the joint position of the athlete and obtain the 2D pixel coordinates of each joint point in each frame. An iterative fitting algorithm is proposed to correct the joint points with errors in recognition by combining the pose characteristics of the athlete. The athletes' motion features are extracted and calculated according to the modified joint points, and the generated human models are applied to compare with the athletes' poses in the video. The experimental results show that the iterative fitting algorithm improves the accuracy and precision of joint point recognition, and the SMPL(skinned multi-person linear) 3D human body model generated after joint point correction is more suitable for reality, which proves the effectiveness of the algorithm for joint point correction.

Recommended Citation

Shen, Ziyi; Yang, Meng; Yang, Chao; Tang, Weidi; Wu, Xie; Liu, Yu; and Sheng, Bin (2023) "Method for Extracting Data During Flight Phase of Ski Jumping Based on Monocular Video," Journal of System Simulation: Vol. 35: Iss. 9, Article 17.
DOI: 10.16182/j.issn1004731x.joss.22-1408
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss9/17

First Page

2035

Last Page

2044

CLC

TP391.9

Recommended Citation

Shen Ziyi, Yang Meng, Yang Chao, et al. Method for Extracting Data During Flight Phase of Ski Jumping Based on Monocular Video[J]. Journal of System Simulation, 2023, 35(9): 2035-2044.

Corresponding Author

Yang Meng

DOI

10.16182/j.issn1004731x.joss.22-1408