Research on the Application of Behavioral Image Feature Capture in Basketball Game Video

In order to realize intelligent image recognition of foul behavior in basketball games, this paper designs a feature capture method of video foul behavior based on improved bilateral filtering algorithm. Adaptive bilateral filtering is used to denoise the video image, and the optical flow feature and HOG feature of the behavior in the denoised image are obtained by image combination feature extraction method, which is fused to a combined eigenvector. The combined features were taken as the target recognition samples, and the multi-back propagation neural network was used to identify the foul behavior features. The particle filter was used to capture the video features and identify the location of the video behavior features. The experimental results show that this method can accurately capture the changes of video behavior characteristics, and has applicable performance in the identification of foul behavior in basketball matches.