系统仿真学报 ›› 2023, Vol. 35 ›› Issue (9): 2035-2044.doi: 10.16182/j.issn1004731x.joss.22-1408

• 论文 • 上一篇    下一篇

基于单目视频的跳台滑雪飞行阶段数据提取方法

沈梓祎1(), 杨猛1,2(), 杨超1, 唐伟棣3, 伍勰3, 刘宇3, 盛斌4   

  1. 1.北京林业大学 信息学院, 北京 100083
    2.国家林业草原林业智能信息处理工程技术研究中心, 北京 100083
    3.上海体育学院, 上海 200438
    4.上海交通大学 计算机科学与工程系, 上海 200240
  • 收稿日期:2022-11-23 修回日期:2023-01-30 出版日期:2023-09-25 发布日期:2023-09-19
  • 通讯作者: 杨猛 E-mail:shenzyiii@foxmail.com;yangmeng@bjfu.edu.cn
  • 第一作者简介:沈梓祎(1998-),女,硕士生,研究方向为图像与视频处理、虚拟现实。E-mail:shenzyiii@foxmail.com
  • 基金资助:
    国家重点研发计划(2019YFC1521104)

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

Shen Ziyi1(), Yang Meng1,2(), Yang Chao1, Tang Weidi3, Wu Xie3, Liu Yu3, Sheng Bin4   

  1. 1.School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
    2.Engineering Research Center for Forestry-Oriented Intelligent Information Processing of National Forestry and Grassland Administration, Beijing 100083, China
    3.Shanghai Institute of Physical Education, Shanghai 200438, China
    4.Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2022-11-23 Revised:2023-01-30 Online:2023-09-25 Published:2023-09-19
  • Contact: Yang Meng E-mail:shenzyiii@foxmail.com;yangmeng@bjfu.edu.cn

摘要:

针对跳台滑雪运动难度系数高,穿戴式传感器等入侵式设备易发生危险且价格昂贵而导致该运动数据提取困难的问题,提出了一种基于单目视频的跳台滑雪飞行阶段的数据提取方法。针对单目视频存在畸变和画面背景杂乱的问题进行预处理,通过标定相机参数对拍摄画面进行畸变矫正,并使用帧间差分法去除背景;利用OpenPose人体姿态识别库对运动员的关节位置进行初步识别,得到每一帧各个关节点的二维像素坐标;结合跳台滑雪运动员的姿态特性,针对识别出现误差的关节点,提出一种迭代拟合算法对其进行修正;根据修正后的关节点对运动员的运动特征进行提取与计算,并应用生成的人体模型与视频中运动员姿态进行动作比对。实验结果表明,迭代拟合算法提高了关节点识别准确率和识别精度,且修正关节点后生成的SMPL(skinned multi-person linear)三维人体模型更加贴合实际,证明了该算法对关节点修正的有效性。

关键词: 跳台滑雪飞行阶段, 人体关节点检测, 坐标修正, 二维轨迹提取, 三维人体模型对比

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 2Dpixel 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.

Key words: flight phase of ski jumping, human joint point detection, coordinate correction, 2D track extraction, comparison of 3D human body model

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