Frame based approach for automatic event boundary detection of soccer video using optical flow

Due to rapid growth of digital contents, there has been an increasing demand of summarized videos to save time and other network resources. Automated soccer video analysis is a challenging due to involvement of more actors and rapid movements of players and camera. It is necessary first to detect various events of the video precisely before analyzing and labeling them. This paper proposes frame based approach for the automatic demarcation of events of the soccer video. However this task is very challenging due to variety of soccer leagues, various illumination and ground conditions. To overcome such issues we propose method which is invariant to such conditions and can successfully demarcate the soccer events. We exploit optical flow techniques to measure the motion. We introduce change in optical flow to extract the behavior of an event over the video span. Later, adaptive threshold is computed based on change in optical flow. We conducted number of simulations with variety of videos to validate the method. Proposed method achieves nearly 90% of accuracy and found robust in spite of illumination variation.