Abstract
In the field of computer vision, high-dynamic dance motion recognition is a difficult problem to solve. Its goal is to recognize human motion by analyzing video data using image processing and classification recognition technology. Video multifeature fusion has sparked a surge in research in a variety of fields. Several pixel points that can be distinguished and displayed in several adjacent images that can reflect their characteristics are referred to as multifeature fusion. It is responsible for a significant portion of the similarity results between the two video segments. Motion recognition relies heavily on video multifeature fusion, which has a direct impact on the robustness and accuracy of recognition results. The directional gradient histogram features, optical flow direction histogram features, and audio features extracted from dance video are used to characterize dance movements after all of the characteristics of dance movements have been considered. This paper focuses on the high-dynamic dance action recognition method based on video multifeature fusion, which aims to combine high-dynamic dance action recognition and video multifeature fusion.
Highlights
Video information has become widely used in many fields as a result of the development of computer vision and video image processing technology [1]
The actions in the dance image video are recognized, and the action model is further established according to the recognition results to generate the character actions in the game, so as to greatly enhance the user experience effect. e research on human motion recognition in China started relatively late, but it developed rapidly
In the field of human motion recognition, some significant research achievements have been made after years of development. e research has broadened from simple action analysis and recognition in a simple background to multiperson complex actions in a complex background
Summary
Video information has become widely used in many fields as a result of the development of computer vision and video image processing technology [1]. After fully considering the characteristics of dance movements, the directional gradient histogram features, optical flow direction histogram features, and audio features extracted from dance video are used to characterize dance movements. Is paper will calculate the optical flow of the image sequence of dance action video after framing in order to extract a set of key frames with less redundancy and can summarize the video content. E directional gradient histogram features, optical flow direction histogram features, and audio features extracted from dance video are used to characterize dance movements after all of the characteristics of dance movements have been considered.
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