Research on Object Tracking Based on Graph Model in Sports Video

摘要

This article is about object tracking based on graph modeling. Object tracking is usually initialized by object detection methods. The fundamental hypothesis is that the object's pattern can be separated from its surrounding background sufficiently. However, for some objects, e.g., the ball in broadcast soccer videos, it is hard to extract effective features to detect the ball in a single video frame. The strategy adopted here is to identify the object's candidate regions in several consecutive frames, and then use a graph to construct the relationship between candidate regions. Finally, a Viterbi algorithm is used to extract the optimal path of the graph as the object's trajectory. This process is called short-term tracking. Then, it is used to initialize a Kalman filter to perform long-term tracking. In the process of tracking, the tracked region is verified to determine whether tracking is a failure, and short-term tracking is restarted if a failure happens.