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

doi:10.16182/j.issn1004731x.joss.22-1408

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 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

CLC Number:

TP391.9

Shen Ziyi, Yang Meng, Yang Chao, Tang Weidi, Wu Xie, Liu Yu, Sheng Bin. Method for Extracting Data During Flight Phase of Ski Jumping Based on Monocular Video[J]. Journal of System Simulation, 2023, 35(9): 2035-2044.

Figures/Tables 16

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Table 1

Joint angles

关节角	角度
$α 0$	39.73
$α 1$	53.62
$α 2$	40.58
$α 3$	22.76
$α 4$	30.86

Table 1

Fig. 11

Fig. 12

Fig. 13

Table 2

Fig. 14

References 20

1	Andriluka M, Roth S, Schiele B. Pictorial Structures Revisited: People Detection and Articulated Pose Estimation[C]//2009 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ, USA: IEEE, 2009: 1014-1021.
2	Wang Jingdong, Sun Ke, Cheng Tianheng, et al. Deep High-resolution Representation Learning for Visual Recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 43(10): 3349-3364.
3	Xiao Bin, Wu Haiping, Wei Yichen. Simple Baselines for Human Pose Estimation and Tracking[C]//Computer Vision-ECCV 2018. Cham: Springer International Publishing, 2018: 472-487.
4	Cao Zhe, Simon T, Wei S E, et al. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Piscataway, NJ, USA: IEEE, 2017: 1302-1310.
5	Yu Changqian, Xiao Bin, Gao Changxin, et al. Lite-HRNet: A Lightweight High-resolution Network[C]//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Piscataway, NJ, USA: IEEE, 2021: 10435-10445.
6	Zhao Tianhao, Li Songnan, Ngan K N, et al. 3-D Reconstruction of Human Body Shape From a Single Commodity Depth Camera[J]. IEEE Transactions on Multimedia, 2019, 21(1): 114-123.
7	Xu Yuanlu, Zhu Songchun, Tung T. DenseRaC: Joint 3D Pose and Shape Estimation by Dense Render-and-compare[C]//2019 IEEE/CVF International Conference on Computer Vision (ICCV). Piscataway, NJ, USA: IEEE, 2019: 7759-7769.
8	Kocabas M, Athanasiou N, Black M J. VIBE: Video Inference for Human Body Pose and Shape Estimation[C]//2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Piscataway, NJ, USA: IEEE, 2020: 5252-5262.
9	Loper M, Mahmood N, Romero J, et al. SMPL: A Skinned Multi-person Linear Model[J]. ACM Transactions on Graphics, 2015, 34(6): 248.
10	Bogo F, Kanazawa A, Lassner C, et al. Keep It SMPL: Automatic Estimation of 3D Human Pose and Shape From a Single Image[C]//Computer Vision-ECCV 2016. Cham: Springer International Publishing, 2016: 561-578.
11	Pavlakos G, Choutas V, Ghorbani N, et al. Expressive Body Capture: 3D Hands, Face, and Body From a Single Image[C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Piscataway, NJ, USA: IEEE, 2019: 10967-10977.
12	Santesteban I, Garces E, Otaduy M A, et al. SoftSMPL: Data-driven Modeling of Nonlinear Soft-tissue Dynamics for Parametric Humans[J]. Computer Graphics Forum, 2020, 39(2): 65-75.
13	李琪, 墨瀚林, 王向东, 等. 短道速滑场景下的多目标跟踪与运动仿真[J]. 系统仿真学报, 2021, 33(5): 1039-1050.
	Li Qi, Mo Hanlin, Wang Xiangdong, et al. Multiple Object Tracking and Kinematic Simulation for Short Track Speed Skating[J]. Journal of System Simulation, 2021, 33(5): 1039-1050.
14	Elfmark O, Ettema G, Groos D, et al. Performance Analysis in Ski Jumping with a Differential Global Navigation Satellite System and Video-based Pose Estimation[J]. Sensors, 2021, 21(16): 5318.
15	伍勰, 曲毅, 刘思平, 等. 跳台滑雪技术生物力学智能分析与反馈系统的研发与应用[J]. 中国体育科技, 2021, 57(12): 3-8.
	Wu Xie, Qu Yi, Liu Siping, et al. An Intelligent Motion Capture and Feedback System Developed for Ski Jumping Technique Analysis[J]. China Sport Science and Technology, 2021, 57(12): 3-8.
16	Bessone V, Petrat J, Schwirtz A. Ground Reaction Forces and Kinematics of Ski Jump Landing Using Wearable Sensors[J]. Sensors, 2019, 19(9): 2011.
17	曹峰锐, 伍勰, 唐伟棣, 等. 跳台滑雪起跳和早期飞行阶段生物力学研究进展[J]. 北京体育大学学报, 2022, 45(1): 35-44.
	Cao Fengrui, Wu Xie, Tang Weidi, et al. A Systematic Review of Research on the Biomechanics of Take-off and Early Flight of Ski Jumping[J]. Journal of Beijing Sport University, 2022, 45(1): 35-44.
18	王蔚, 冯亚琴, 杨再兴, 等. 基于体感交互设备的人体重心计算方法[J]. 数据采集与处理, 2018, 33(4): 595-602.
	Wang Wei, Feng Yaqin, Yang Zaixing, et al. Calculation Method for Human Center of Gravity Based on Somatosensory Interaction[J]. Journal of Data Acquisition and Processing, 2018, 33(4): 595-602.
19	应响. 基于Openpose的姿态匹配研究及其在体育教学中的应用[D]. 南京: 南京师范大学, 2021.
20	Vodičar Janez, Čoh Milan, Jošt Bojan. Kinematic Structure at the Early Flight Position in Ski Jumping[J]. Journal of Human Kinetics, 2012, 35(1): 35-45.

算法	PCKh	mAP
OpenPose	63.24	67.91
本文修正后	78.56	85.08
Lite-HRNet	66.13	70.27
本文修正后	79.52	83.26

[1]	Yuan Biao, Huang Yourui, Xu Shanyong, Rong Xue. Construction and Application of Digital Twin System for Optical Fiber Secondary Coating Workshop [J]. Journal of System Simulation, 2023, 35(9): 2011-2022.
[2]	Guo Runxia, Wang Yifu. Aircraft Assignment Method for Optimal Utilization of Maintenance Intervals [J]. Journal of System Simulation, 2023, 35(9): 1985-1999.
[3]	Jiao Songming, Shou Yunfeng, Bai Jianpeng, Wang Zhu. Research on Hierarchical Motion Planning Method for UAV Substation Inspection [J]. Journal of System Simulation, 2023, 35(9): 1975-1984.
[4]	Zhang Hongli, Deng Jingshuang. Research on Artificial Population Generation and Application Based on Genetic Algorithm [J]. Journal of System Simulation, 2023, 35(9): 1965-1974.
[5]	He Yulin, Chen Jiaqi, Xu Hepeng, Huang Zhexue, Yin Jianfei. Data Generation Model-based Synthetic Sample Imputation Method [J]. Journal of System Simulation, 2023, 35(9): 1948-1964.
[6]	Dong Qingqing, Wu Hao, Qian Wenhua, Kong Fengling. RGB-D Saliency Object Detection Based on Cross-refinement and Circular Attention [J]. Journal of System Simulation, 2023, 35(9): 1931-1947.
[7]	Wang Man, Li Dapeng, Ding Lianghui, Zhu Tianlin. Formation Obstacle Avoidance Algorithm Based on Joint Virtual Sub-target and Boundary Force [J]. Journal of System Simulation, 2023, 35(9): 1918-1930.
[8]	Chen Dejun, Fang Zihao, Zeng Yunxiu, Xu Kai. Deceptive Path Planning in Fog of War [J]. Journal of System Simulation, 2023, 35(9): 1895-1908.
[9]	Ma Shanzhi, Wang Hongliang, He Hua, Lun Weicheng. Research on Support Effectiveness Evaluation Method of Equipment Systems Based on PERT and ABMS [J]. Journal of System Simulation, 2023, 35(9): 1837-1846.
[10]	Peng Yong, Zhang Miao, Hu Yue. Cloud-Edge Collaborative Service Architecture for LVC Training System [J]. Journal of System Simulation, 2023, 35(9): 1825-1836.
[11]	Tan Zhao, Lin Wu, JiuYang Tao, Shuai Li. Metaverse Concept and Its Military Application [J]. Journal of System Simulation, 2023, 35(7): 1405-1420.
[12]	Xiaofeng Wang, Taiqian Shen, Yuan Liu. Research on Dynamic Simulation Technology for Satellite Internet [J]. Journal of System Simulation, 2023, 35(7): 1472-1486.
[13]	Miaomiao Ma, Lipeng Dong, Xiangjie Liu. Energy Management Strategy of Multi-agent Microgrid Based on Q-learning Algorithm [J]. Journal of System Simulation, 2023, 35(7): 1487-1496.
[14]	Jian Xu, Xin Song, Xiuping Liu, Bo Chen, Huanying Yan. Modeling and System Realization of Assembly Robot Based on Digital Twin [J]. Journal of System Simulation, 2023, 35(7): 1497-1507.
[15]	Lizhen Du, Tao Ye, Yuhao Wang, Yajun Zhang, Zifeng Xuan. Improved Particle Swarm Algorithm of Unrelated Parallel Batch Scheduling Optimization [J]. Journal of System Simulation, 2023, 35(7): 1549-1561.