Sports Video Segmentation using Spectral Clustering

Journal of Multimedia

关键词: Sports Video;    For Sports Video Analysis;    Video Processing;   

Others  :  945828
DOI  :  10.4304/jmm.9.7.873-878

【 摘 要 】

With the rapid development of the computer and multimedia technology, the video processing technique is applied to the field of sports in order to analyze the sport video. For sports video analysis, how to segment the sports video image has become an important research topic. Nowadays, the algorithms for video image segmentation mainly include neural network, K-means and so on. However, the accuracy and speed of these algorithms for moving objects segmentation are not satisfied, and easily influenced by the irregular movement of the object and illumination, etc. In view of this, this paper proposes an algorithm for object segmentation in sports video image sequence, based on the spectral clustering. This algorithm simultaneously considers the pixel level visual feature and the edge information of the neighboring pixels to make the calculation of similarity is more intuitive and not affected by factors such as image texture. When clustering the image feature, the proposed method: (1) preprocesses video image sequence and extracts the image feature. (2)Using weight function to build and calculate the similar matrix between pixels. (2) Extract feature vector. (3) Perform clustering using spectral clustering algorithm to segment the sports video image. The experimental results indicate that the method proposed in this paper has the advantages, such as lower complexity, high computational effectiveness, low computational amount, and so on. It can get better extraction effects on video image

【 授权许可】

   
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