Efficient Shot Boundary Detection Based on Scale Invariant Features

Abstract

Shot boundary detection is an important fundamental process in video analysis. A novel shot boundary detection is proposed in this paper. To improve the performance of the algorithm and reduce the computational cost, frames that are clearly not shot boundaries are first removed from the original video. After that, new features are proposed to capture the changing statistics of different kinds of shot transitions so as to identify, not only abrupt shot transitions, but also gradual transitions accordingly. At last, use different algorithms for different kinds of shot transitions to help us to get a better solution for shot boundary detection problem. Numerical experiments in a variety of videos demonstrate that our method is capable of accurately detecting shot transitions, and could greatly reduce the computational cost.