Video analysis is an essential process to segment and summarize sports videos automatically. In this paper, we propose fast and simple computer vision algorithms which can be employed to an event segmentation system for basketball broadcasting videos. In our approach, camera panning is estimated by the optical flow estimation and flow segmentation algorithms. For recognizing shot classes and clock digits, Convolutional Neural Network (CNN) is used. By the experiment, it is observed that our algorithms operate in real time and are accurate to be adapted to the event segmentation system.