Gymnastics Athlete Aerobics Posture Analysis Video Dataset

In the current sports industry, athlete posture analysis and performance optimization are becoming increasingly important. However, traditional manual analysis methods are subjective and inconsistent, failing to meet the demand for quick and accurate analysis. This dataset aims to solve the technical bottleneck in aerobics posture analysis by providing standardized video data to improve the accuracy and objectivity of posture recognition. The video data is collected using high-definition camera equipment in different gyms, covering various aerobics movements. In the processing workflow, multiple rounds of annotation and expert review are employed to ensure high quality and consistency of the data. Data preprocessing includes motion trajectory extraction, background noise suppression, and action segmentation, ultimately stored in MP4 format and organized by action category. The annotation team consists of sports professionals and data scientists, a total of 20 people, ensuring professionalism and scientific accuracy. The quality of this dataset maintains high annotation precision and consistency by using innovative posture annotation methods and data enhancement techniques to achieve efficient and accurate action recognition. It can significantly enhance the performance indicators of aerobics posture analysis, offering higher action precision and broader applicability compared to other similar datasets. The data scarcity is reflected in its unique in-depth coverage of sports projects and diverse action classification. Additionally, this dataset is suitable for posture analysis in different sports projects, with good scalability and generality.