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Wipe scene change detection and classification in video sequences

机译:擦除视频序列中的场景变化检测和分类

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摘要

There is an urgent 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 novel algorithm for wipe scene change detection in uncompressed and MPEG-1 compressed video sequences using statistical and geometric properties of each image. An efficient algorithm is also proposed to estimate statistical features in compressed video without full frame decompression. From uncompressed and MPEG compressed frames, thumbnails are obtained where pixels are the averages and variances of luminance values of macroblocks. Differences between thumbnails are computed and thresholded, and straight lines are detected in the resulting binary images. Persistence and motion of these lines indicate the presence of a shot transition using wipes. Results on video of various content types are reported and validated with the proposed schemes. Furthermore, results show that the accuracy of the detection is above 95% for uncompressed and above 90% for MPEG-1 compressed video.
机译:为了索引,快速检索和场景分析,迫切需要从视频中自动提取关键信息。为了支持这一愿景,必须开发可靠的场景变化检测算法。本文介绍了一种新颖的算法,该算法利用每个图像的统计和几何特性,对未压缩和MPEG-1压缩视频序列中的擦拭场景变化进行检测。还提出了一种有效的算法来估计压缩视频中的统计特征而无需全帧解压缩。从未压缩和MPEG压缩帧中,获得缩略图,其中像素是宏块亮度值的平均值和方差。计算缩略图之间的差异并将其设置为阈值,并在生成的二进制图像中检测直线。这些线条的持续性和运动性表明存在使用擦拭进行镜头过渡的情况。报告了各种内容类型的视频结果,并使用提出的方案进行了验证。此外,结果表明,未压缩的检测精度高于95%,而MPEG-1压缩视频的检测精度高于90%。

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