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

There is an increasing need to extract key information automatically from video for the purposes of indexing, fast retrieval and scene analysis. To support this vision, reliable scene change detection algorithms must be developed. This paper describes a unified approach for scene change detection in uncompressed and MPEG-2 compressed video sequences using statistical properties of each image. An efficient algorithm is proposed to estimate statistical features in compressed video without full frame decompression and used these features with the uncompressed domain algorithms to identify scene changes in compressed video. Proposed scheme aims at detecting abrupt transitions and gradual transitions in both uncompressed and MPEG-2 compressed video using a single framework. Results on video of various content types are reported and validated. Furthermore, results show that for uncompressed video the accuracy of the detected transition region is above 98% and above 95% for MPEG-2 compressed video.