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Simulation of athletes’ motion detection and recovery technology based on monocular vision and biomechanics
- Source :
- Journal of Intelligent & Fuzzy Systems. 40:2241-2252
- Publication Year :
- 2021
- Publisher :
- IOS Press, 2021.
-
Abstract
- Athletes’ sports detection has a heavy pressure on athletes’ training and post-injury rehabilitation. In the traditional mobilization test, there is no effective combination of exercise and rehabilitation, which directly leads to the athlete’s physical health cannot be guaranteed. Based on this, this study combines the current situation of the athletes’ field and the training ground, and uses monocular vision as the video input interface, and combines the monocular vision technology in the research. Moreover, in the research, this paper combines the human body model to construct an athlete’s human body model that adapts to monocular vision. At the same time, this paper combines the image processing technology to transform the image of the monocular visual athlete into a skeleton model, so as to realize the modeling of the athlete’s movement. In addition, this paper combines the model to explore the indoor and outdoor athlete recovery techniques and validates the model by experiment. The research shows that the research model has certain effects, which can meet the actual needs, and can provide theoretical reference for subsequent related research.
- Subjects :
- Statistics and Probability
medicine.medical_specialty
biology
Computer science
Athletes
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
General Engineering
Biomechanics
020206 networking & telecommunications
Motion detection
02 engineering and technology
biology.organism_classification
Physical medicine and rehabilitation
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
medicine
020201 artificial intelligence & image processing
Monocular vision
Subjects
Details
- ISSN :
- 18758967 and 10641246
- Volume :
- 40
- Database :
- OpenAIRE
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Accession number :
- edsair.doi...........751cba434c109782183b831d44373295
- Full Text :
- https://doi.org/10.3233/jifs-189222