Developing High-Level Representations of Video Clips using VideoTrails

A high-level representation of a video clip comprising information about its physical and semantic structure isnecessary for providing appropriate processing, indexing and retrieval capabilities for video databases. We describe
a novel technique which reduces a sequence of MPEG encoded video frames to a trail of points in a low dimensional
space. In our earlier work, we presented techniques applicable in 3-D, but in this paper, we describe techniques that
can be extended to higher dimensions where improved performance is expected. In the low-dimensional space, we
can cluster frames, analyze transitions between clusters and compute properties of the resulting trail. Portions of the
trail can be classi ed as either stationary or transitional, leading to high-level descriptions of the video. Tracking the
interaction of clusters over time, we lay the groundwork for the complete analysis and representation of the video's
physical and semantic structure.