Shot Boundary Detection Method for News Video

It is very important to detect shot boundary accurately and quickly in a large number of news video data. Therefore, we proposed a new method with dual-detection model. The method is divided into two stages, i.e. pre-detection and re-detection. In the pre-detection stage, the uneven blocked differences based on the feature of human vision are presented and used in adaptive binary search to detect shot boundaries. In the re-detection round, Speeded Up Robust Features (SURF) method is applied to exclude false detections. The experimental results show that this method can detect abrupt boundaries of news video quickly and accurately.