Football Match Video Object Detection And Tracking

Nowadays, the programs of sports video are becoming more and more popular. Therefore, it possesses high actual meaning and commerce worthiness to analyse on the sports video. In this paper, soccer video is analyzed as an example. Detection and tracking of objects in the soccer video are studied. Here the objects we pay attention to include soccer players, ball and court lines. It is proved actually that these three kinds of objects contain a lot of information of the game.According to the difference in color and sharp, two different measures are adopted to detect the objects we focus on in this paper. About the detection for court lines, this paper discusses and compares the segment effects produced by the Top-Hat transform and the edge detectors. Insensitiveness to the noise, Hough transform is used to obtain coordinate parameters of lines. A method is discussed to get start and end points of lines. About the detection for players and ball, this paper advances a series of algorithms to segment, distill and recognize the areas of players and ball. The problems in segmented images that a clearance often exists in a player area and the conglutination between players and lines are discussed and an appropriate method is advanced to resolve it. Experimental results show that the detection algorithms advanced in this paper is robust to the noise. The results of objects detection are gratifying for various soccer video.This paper present an algorithm of tracking the objects in the soccer video based on Kalman filter. The tracking history is encoded into state parameter of the filter. The estimated state parameter will be used to reduce search area for model matching. The problems appearing in the tracking process about players matching and players sheltering are studied and methods to resolve them are present. This paper advances that tracking the court lines by estimating coordinate parameters of lines. And the parameters in Hough transform are restricted based on the estimated coordinate parameters to reduce the computation. Experimental results show that the tracking strategy presented in this paper is effective to track objects in soccer video.The process technologies for the sports video in this paper are already applied in actual projects.