Tennis Video Analysis Technology

With the rapid increase of the amount of digital videos, the problem how to find useful information has become much urgent. This paper focuses on content-based video analysis and retrieval technology in sports video domain. The aim is to process, analyze and understand video content with computer to construct index and structure for facilitating user's access, which is provided with important academic appeals and commercial potentials.This paper takes tennis video as research object, and discusses several problems in the process of content-based video retrieval, including shot boundary detection, key frame selection, feature extraction and shot classification, audio type classification, interesting events detecting.Shot boundary detection is the first step of video processing, starting from a generalization of methods of shot boundary detection, this paper analysised an algorithm for detecting abrupt video shot boundaries based on method of adaptive threshold, and an algorithm for gradual shot boundaries detecting using the mean gray level (MGL) of image.Based on abstracting typical frames of video shots, this paper proposed a shot classification method which is based on K-means cluster processing combined with main color rate computing. After that, this paper used a algorithm for detecting court class based on court color.For play shots, important auditory features including both ball hitting and cheer are detected by using SVM. Afterwards, audio features are applied into play shots for interesting events detecting in tennis video.Finally, This paper implements a prototype system for content-based tennis video anlysis by Visual C++ 6.0 and Matlab 7.0, and the experiments have demonstrate that all these methods are effective.