Abstract
The purpose of video key frame extraction is to use as few video frames as possible to represent as much video content as possible, reduce redundant video frames, and reduce the amount of computation, so as to facilitate quick browsing, content summarization, indexing, and retrieval of videos. In this paper, a method of dance motion recognition and video key frame extraction based on multifeature fusion is designed to learn the complicated and changeable dancer motion recognition. Firstly, multiple features are fused, and then the similarity is measured. Then, the video sequences are clustered by the clustering algorithm according to the scene. Finally, the key frames are extracted according to the minimum amount of motion. Through the quantitative analysis and research of the simulation results of different models, it can be seen that the model proposed in this paper can show high performance and stability. The breakthrough of video clip retrieval technology is bound to effectively promote the inheritance and development of dance, which is of great theoretical significance and practical value.
Highlights
With the continuous progress of multimedia technology and computer network, video and images show more positive significance in daily life, and the amount of video image data is increasing geometrically [1]. erefore, for video data, how to index it and retrieve it quickly and accurately has become an urgent demand [2]
This paper proposes a multifeature fusion-based video key frame extraction method and applies it to dance action recognition
Most of the more complicated methods measure the similarity between any two frames in the shot by means of some underlying features such as color, texture, and motion information and divide all frames in the shot into different classes by combining threshold or clustering and select representative frames from each class as key frames. erefore, this paper proposes a method of dance motion recognition and video key frame extraction based on multifeature fusion, which is used to learn complex and changeable dance motion recognition
Summary
With the continuous progress of multimedia technology and computer network, video and images show more positive significance in daily life, and the amount of video image data is increasing geometrically [1]. erefore, for video data, how to index it and retrieve it quickly and accurately has become an urgent demand [2]. Its purpose is to analyze video data using image processing [6,7,8] and classification recognition technology [9,10] to recognize human motion [11]. This paper proposes a multifeature fusion-based video key frame extraction method and applies it to dance action recognition. The research of motion recognition method based on dance video will play a positive role in the research of human motion recognition in a large number of real and complex environments, enriching the application fields of motion recognition technology [21]. This paper shows the feature extraction process and model in the key frame extraction method of music and dance video and applies the feature fusion and recognition method to the key frame extraction of music and dance video. e simulation results show that the method proposed in this paper has high performance and accuracy
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