基于动态时间翘曲和均值移位的镜头边界检测视频摘要

Ahmed Khazaal Sulaiman, S. A. Mahmood
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引用次数: 1

摘要

最近,随着多媒体通信技术和低成本存储设备的发展,网络空间中的视频数量不断增加;拥有快速浏览和搜索庞大多媒体数据库的能力已成为必须的。在此背景下,基于视频摘要的视频检索成为一个亟待解决的关键问题。镜头边界检测SBD方法的主要目标是在镜头边界检测方面检测视频序列中连续帧之间的过渡。因此,基于内容的视频检索采用了信息丰富的镜头。本文提出了一种新的镜头边界检测方法,主要存在两个问题;静态和动态对象具有静态和动态相机运动。该方法采用动态时间翘曲DTW方法来识别序列帧之间的差异。基于均值移位技术捕获帧内和帧间序列的突变和渐变变化。实验结果表明,本文提出的基于镜头边界检测的关键帧提取方法具有较高的提取效率,提取的帧信息量大,冗余少。
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Shot Boundaries Detection Based Video Summary Using Dynamic Time Warping and Mean Shift
Recently, an increasing in videos amount presents in cyberspace in conjunction with growth of multimedia communications and technologies, and low-cost storage devices; it has become obligatory to have the capability to rapidly browse and search through huge multimedia databases. In this context, video summarization-based video retrieval has become a critical issue needs to be addressed. The main objective of shots boundary detection SBD methods pursues to detect the transitions between consecutive frames along video sequences in term of shots boundary detection. Hence, shots with abundant information are employed in the content-based video retrieval. This paper presents a new approach for shot boundary detection with two main challenges; static and dynamic objects with static and dynamic camera motion. The proposed method employed the Dynamic Time Warping DTW method for identifying the differences between sequenced frames. The abrupt and gradual changes are captured along frame’s sequences within and between shots based on mean shift technique. From the experiments, the proposed shot boundary detection based key frame extraction method exhibits an efficient performance represented by more informative frames with less redundancy.
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