Novel video keyframe extraction using KPE vector quantization with assorted similarity measures in RGB and LUV color spaces

Sudeep D. Thepade, Pritam H. Patil
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引用次数: 13

Abstract

In the current era, most of the digital information is in the form of multimedia with a giant share of videos. Videos do have audio and visual content where the visual content has number of frames put in a sequence. Most of the consecutive frames do have very little discriminative contents. In video summarization process, several frames containing similar information do need to get processed. This leads to redundant slow processing speed and complexity, time consumption. Video summarization using key frames can ease the speed up of video processing. In this paper, novel key frames extraction method is proposed with Kekere's Proportionate Error (KPE) codebook generation techniques of vector quantization with ten different codebook sizes and two color spaces (RGB and KLUV). Experimentation done with help of the test bed of videos has shown that higher codebook sizes of KPE have given better completeness in key frame extraction for video summarization. The LUV color space with Euclidean Distance with 512 codebook size gives best performance. In square chord Distance, Mean Square Error and Euclidean Distance LUV color space gives better completeness than RGB color space for proposed KPE based video Key frame Extraction.
基于RGB和LUV色彩空间相似度度量的KPE矢量量化视频关键帧提取方法
在当今时代,大多数数字信息都是以多媒体的形式存在的,其中视频占据了巨大的份额。视频确实有音频和视觉内容,其中视觉内容具有按顺序放置的帧数。大多数连续帧确实有很少的判别内容。在视频摘要过程中,确实需要对包含相似信息的多个帧进行处理。这就导致冗余处理速度慢、复杂、费时。利用关键帧进行视频摘要,可以降低视频处理的速度。本文提出了一种新的关键帧提取方法,该方法采用Kekere比例误差(KPE)码本生成技术,采用10种不同码本大小和两种颜色空间(RGB和KLUV)进行矢量量化。借助视频测试平台进行的实验表明,KPE码本尺寸越大,视频摘要关键帧提取的完整性越好。具有512码本大小的欧几里得距离的LUV色彩空间具有最佳性能。在所提出的基于KPE的视频关键帧提取中,LUV色彩空间在平方弦距离、均方误差和欧氏距离方面比RGB色彩空间具有更好的完整性。
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