Method of Quantifying and Analyzing the Characteristics of Sports Action 

Caizhen Song*, Lifang Zhang

Department of Physical Education, Changsha Normal University, Changsha, 410100, China

Abstract: In order to improve the ability of quantitative analysis and pattern recognition of sports movement features, a method of sports movement feature quantization and pattern analysis based on computer vision image analysis is proposed. Based on wavelet multilayer decomposition and feature transformation, a model of feature extraction and quantization pattern recognition of sports action image is constructed. The method of one-dimensional wavelet transform is used to decompose the motion feature of sports action image visually. Combined with edge pixel reconstruction and Harris corner detection method, the sports action image is segmented, and the feature quantization analysis and pattern recognition of the sub-block pixel of the sports action image are carried out to achieve image enhancement. The wavelet multilayer decomposition and feature transformation are used to reconstruct the 3D feature of sports action image, and the multi-scale Retinex algorithm is used to extract the feature points of sports action, and to realize the quantization pattern recognition of sports action image. The simulation results show that the algorithm has higher accuracy and better ability of quantization and pattern analysis of sports action image. The ability of dynamic recognition and planning analysis of sports action is improved.

Keywords: Sports; Feature analysis; Image; Pattern recognition; Wavelet analysis; Computer vision image