Shot boundary detection in videos using robust three-dimensional tracking

The use of three dimensional information from video is rare in the video analysis literature due to the inherent difficulties of extracting accurate 3D measurements from a single view of a scene. Several methods have been published in recent years, however, that attempt to solve such a problem. They all use the same underlying meaning of exploiting camera motion in order to measure the parallax of visible objects in the scene. In this paper, we employ the use of such algorithms towards solving the problem of automatic shot boundary detection. The idea is to extract salient features from a video sequence and track them over time in order to estimate shot boundaries within the video. We apply many ideas from previously published SLAM techniques in order to model the inherent three dimensional structure of a scene, and accurately track various salient features across frames. We detect shot boundaries in videos by observing the system's ability to successfully track features across frames.