Sports Video Image Analysis Application Based on BP Neural Network Algorithm

T. Xia, Feng Liu
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Abstract

Human motion analysis is one of the main directions in the field of computer vision in recent years. Especially in the emerging field of competitive sports analysis. The purpose of this paper is to study the application of sports video image analysis based on BP neural network algorithm. The node number of input layer, output layer and hidden layer of BP neural network classifier is selected to establish the neural network classifier model. Select parameters such as learning rate and convergence error. The fusion features of LBP histogram reflecting motion behavior and motion speed are taken as the input of BP neural network, and the type of motion behavior is taken as the output of the neural network. Through experimental research, it is concluded that the sports behavior recognition algorithm proposed in this paper can achieve good results.
基于BP神经网络算法的体育视频图像分析应用
人体运动分析是近年来计算机视觉领域的主要研究方向之一。尤其是在竞技体育分析这一新兴领域。本文的目的是研究基于BP神经网络算法在体育视频图像分析中的应用。选取BP神经网络分类器的输入层、输出层和隐藏层的节点数,建立神经网络分类器模型。选择学习速率、收敛误差等参数。将反映运动行为和运动速度的LBP直方图的融合特征作为BP神经网络的输入,将运动行为类型作为神经网络的输出。通过实验研究,得出本文提出的运动行为识别算法能够取得较好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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