Video Shot Boundary Detection in Sport Video Using the Scale Invariant Feature Transform

Abstract

The main purpose of shot boundary detection is to detect visual content changes between consecutives frames of a video. In this paper, a new shot boundary detection algorithm is proposed based on the scale invariant feature transform (SIFT). The first stage consists on a top down search scheme to detect the locations of transitions by comparing the ratio of matched features extracted via SIFT for every RGB channel of video frames. A temporal sampling period is used to avoid the frame by frame processing. The overview step provides the changes of matched features ratio all along the video. Secondly, a function is performed to detect the shot boundaries. The proposed method can be used for detecting gradual transitions as well as hard cuts and without requiring any training of the video content in advance. Experiments have been conducted on sports video and show that this algorithm achieves good results in detecting both abrupt and gradual transitions.