Research on the Recognition Algorithm of Basketball Technical Action Based on BP Neural System

Abstract

Vision-based intelligent human action recognition is the most challenging direction in the field of computer vision in recent years. It detects human actions in video sequences, extracts action features and learns action features, and then recognizes human actions in videos. This paper is based on BP neural network’s basketball technique action recognition and experimental verification. First, design a basketball technique action recognition method based on BP neural network, analyze basketball actions, collect relevant test data, and divide the methods of basketball action recognition. Finally, analyze the action characteristics and waveform conditions of the upper- and lower-limb movements of the basketball action and analyze the key basketball action recognition data. The designed classification method realizes the effective recognition of basketball actions; then, the basketball recognition method used in this article is experimentally verified, and the feasibility and effectiveness of the recognition method selected in this article are verified by recognizing basketball technical actions, and the experimental results are carried out. Compared with other related studies, this method proposes a division of unit actions to complete the cycle division of basketball actions. The division results do not include the overlap of other actions, avoiding repeated calculations of actions and greatly reducing the amount of calculation of the system. In addition, the method for the recognition of basketball movement includes the separate recognition of upper- and lower-limb movements, comprehensive consideration of arm and leg movements, and a more comprehensive and accurate analysis of basketball movements.