Using AI Motion Capture Systems to Capture Race Walking Technology at a Race Scene: A Comparative Experiment
Background: This study tested the reliability of the 3D coordinates of human joint points obtained by using an AI motion capture system at a race walking scene. Methods: Using a direct linear transformation (DLT) 3D video recording method, 15 race walking athletes were photographed. We compared the...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/1/113 |
| _version_ | 1797626371443261440 |
|---|---|
| author | Dongtao Zhang Zhongqiu Ji Guiping Jiang Weiwei Jiao |
| author_facet | Dongtao Zhang Zhongqiu Ji Guiping Jiang Weiwei Jiao |
| author_sort | Dongtao Zhang |
| collection | DOAJ |
| description | Background: This study tested the reliability of the 3D coordinates of human joint points obtained by using an AI motion capture system at a race walking scene. Methods: Using a direct linear transformation (DLT) 3D video recording method, 15 race walking athletes were photographed. We compared the average values, standard deviations, and 95% confidence intervals of the multiple correlation coefficients and differences in the 3D coordinate–time curve of the human joint points that were automatically parsed by the AI motion capture system with those that were manually parsed. Results: Except for the left shoulder y coordinates, left hip y and z coordinates, and left toe tip z coordinates, the multiple correlation coefficients between the curve obtained via the automatic analysis and the average curve obtained via the manual analysis of the other coordinates were greater than 0.90, while the difference between the curve obtained via the automatic analysis and the curve obtained via the manual analysis of the left hand, the left wrist, the left hip, and the left toe was less than 0.025 m. Conclusion: The 3D coordinates of the human joint points obtained via the AI motion capture system were highly similar to the average value of the 3D coordinates obtained via the manual analysis, supporting the use of the AI motion capture system as a highly reliable means to capture the technical motion of race walking in the race walking competition context. |
| first_indexed | 2024-03-11T10:09:28Z |
| format | Article |
| id | doaj.art-f94bc39d1c3e40dfb59b87a7ef2c4049 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T10:09:28Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-f94bc39d1c3e40dfb59b87a7ef2c40492023-11-16T14:50:49ZengMDPI AGApplied Sciences2076-34172022-12-0113111310.3390/app13010113Using AI Motion Capture Systems to Capture Race Walking Technology at a Race Scene: A Comparative ExperimentDongtao Zhang0Zhongqiu Ji1Guiping Jiang2Weiwei Jiao3College of P.E. and Sports, Beijing Normal University, Beijing 100875, ChinaCollege of P.E. and Sports, Beijing Normal University, Beijing 100875, ChinaCollege of P.E. and Sports, Beijing Normal University, Beijing 100875, ChinaPhysical Education Institute, Langfang Normal University, Langfang 065000, ChinaBackground: This study tested the reliability of the 3D coordinates of human joint points obtained by using an AI motion capture system at a race walking scene. Methods: Using a direct linear transformation (DLT) 3D video recording method, 15 race walking athletes were photographed. We compared the average values, standard deviations, and 95% confidence intervals of the multiple correlation coefficients and differences in the 3D coordinate–time curve of the human joint points that were automatically parsed by the AI motion capture system with those that were manually parsed. Results: Except for the left shoulder y coordinates, left hip y and z coordinates, and left toe tip z coordinates, the multiple correlation coefficients between the curve obtained via the automatic analysis and the average curve obtained via the manual analysis of the other coordinates were greater than 0.90, while the difference between the curve obtained via the automatic analysis and the curve obtained via the manual analysis of the left hand, the left wrist, the left hip, and the left toe was less than 0.025 m. Conclusion: The 3D coordinates of the human joint points obtained via the AI motion capture system were highly similar to the average value of the 3D coordinates obtained via the manual analysis, supporting the use of the AI motion capture system as a highly reliable means to capture the technical motion of race walking in the race walking competition context.https://www.mdpi.com/2076-3417/13/1/113AImotion capturevideo analysisrace walkingcontrast experiment |
| spellingShingle | Dongtao Zhang Zhongqiu Ji Guiping Jiang Weiwei Jiao Using AI Motion Capture Systems to Capture Race Walking Technology at a Race Scene: A Comparative Experiment Applied Sciences AI motion capture video analysis race walking contrast experiment |
| title | Using AI Motion Capture Systems to Capture Race Walking Technology at a Race Scene: A Comparative Experiment |
| title_full | Using AI Motion Capture Systems to Capture Race Walking Technology at a Race Scene: A Comparative Experiment |
| title_fullStr | Using AI Motion Capture Systems to Capture Race Walking Technology at a Race Scene: A Comparative Experiment |
| title_full_unstemmed | Using AI Motion Capture Systems to Capture Race Walking Technology at a Race Scene: A Comparative Experiment |
| title_short | Using AI Motion Capture Systems to Capture Race Walking Technology at a Race Scene: A Comparative Experiment |
| title_sort | using ai motion capture systems to capture race walking technology at a race scene a comparative experiment |
| topic | AI motion capture video analysis race walking contrast experiment |
| url | https://www.mdpi.com/2076-3417/13/1/113 |
| work_keys_str_mv | AT dongtaozhang usingaimotioncapturesystemstocaptureracewalkingtechnologyataracesceneacomparativeexperiment AT zhongqiuji usingaimotioncapturesystemstocaptureracewalkingtechnologyataracesceneacomparativeexperiment AT guipingjiang usingaimotioncapturesystemstocaptureracewalkingtechnologyataracesceneacomparativeexperiment AT weiweijiao usingaimotioncapturesystemstocaptureracewalkingtechnologyataracesceneacomparativeexperiment |