The Construction of Adaptive Learning for Sports Based on Aerobics Trajectory Recognition Model. (9th August 2022)
- Record Type:
- Journal Article
- Title:
- The Construction of Adaptive Learning for Sports Based on Aerobics Trajectory Recognition Model. (9th August 2022)
- Main Title:
- The Construction of Adaptive Learning for Sports Based on Aerobics Trajectory Recognition Model
- Authors:
- Xi, Chaojie
- Other Names:
- Chen Miaochao Academic Editor.
- Abstract:
- Abstract : Perceiving the movement track of aerobics is a key element of learning aerobics, but the current aerobics movement is not very professional, the ability to identify the movement track is weak, and improper movement in the movement process is easy to cause physical injury. In order to improve the safety of athletes in bodybuilding training, this paper uses Kinect to hold the coach's body contour, determine the standard level of coaches' sports, and combine the characteristics for aerobics training, so as to improve the sports level of coaches, through data acquisition, data processing, and feature extraction to assist sports learning, as well as human posture recognition. The calculation and recognition of human skeleton joints are completed by two algorithms, which improve the human motion recognition algorithm. The aerobics data collected by Kinect device is specified and digitized, which enhances the robustness of the system and improves the performance of the algorithm and the accuracy of the motion data.
- Is Part Of:
- Journal of function spaces. Volume 2022(2022)
- Journal:
- Journal of function spaces
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-08-09
- Subjects:
- Function spaces -- Periodicals
515.7305 - Journal URLs:
- https://www.hindawi.com/journals/jfs/ ↗
- DOI:
- 10.1155/2022/8339745 ↗
- Languages:
- English
- ISSNs:
- 2314-8896
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23501.xml