A unified approach to scene change detection in uncompressed and compressed video

There is an increasing need to extract key information automatically from v ideo for the purposes of indexing, fast retrieval and scene analysis. To su pport this vision, reliable scene change detection algorithms must be devel oped. This paper describes a unified approach for scene change detection in uncompressed and MPEG-2 compressed video sequences using statistical prope rties of each image. An efficient algorithm is proposed to estimate statist ical features in compressed video without full frame decompression and used these features with the uncompressed domain algorithms to identify scene c hanges in compressed video. Proposed scheme aims at detecting abrupt transi tions and gradual transitions in both uncompressed and MPEG-2 compressed vi deo using a single framework. Results on video of various content types are reported and validated. Furthermore, results show that for uncompressed vi deo the accuracy of the detected transition region is above 98% and above 9 5% for MPEG-2 compressed video.