On fast microscopic browsing of MPEG compressed video

In this paper we address the problem of rapid access to individual shots and frames in MPEG video. We build upon the compressed video processing framework proposed in Yeo (1996) and Yeo and Liu (1995), and propose new and fast algorithms based on an adaptive mixture of approximation techniques for extracting a spatially reduced image sequence of uniform quality from MPEG video across different frame types and also under different motion activities in the scenes. The algorithms execute faster than real-time on a Pentium personal computer. We demonstrate how the reduced images facilitate fast and convenient shot and frame-level video browsing and access, shot level editing and annotation, without the need for frequent decompression of MPEG video. We further propose methods for reducing the auxiliary data size associated with the reduced images through exploitation of spatial and temporal redundancy. The algorithms, tools for browsing and techniques for video processing presented in this paper have been used by many in IBM Research on more than 30 hours of MPEG-1 video for video browsing and analysis, and found to be indispensable.