The application of shot classification based on C4.5 decision tree in video retrieval

In this paper, we classify shots in the level of type in connection with several types of shots. By comparing the differences of low-level features from these types of shots, we extract motion information, color, and pixel differences as features for our experiment. Through the training of C4.5 decision tree, a bridge is built to eliminate the gap from low-level features to high-level semantic, and a good performance of shot classification is achieved.