基于局部二值模式的镜头边界检测视频摘要

S. Kaavya, G. Priya
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引用次数: 2

摘要

视频摘要在互联网用户的生活中起着至关重要的作用,特别是对于那些长期搜索用户感兴趣的特定视频的人来说。为了给用户搜索和检索视频内容提供支持,需要将视频分割成多个镜头,并提取每个镜头的代表性帧作为视频的总结。为此,本文提出了一种镜头边界检测和关键帧提取方法。为了更好地对视频进行总结,采用基于局部二值模式(LBP)的特征提取来检测视频镜头,以识别目标的运动信息。在局部极大值分析的基础上,提出了一种包含镜头显著信息的高效关键帧。所建议的工作的性能使用评估指标进行评估,如Precision、Recall和F1-Measure。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Local Binary Pattern Based Shot Boundary Detection for Video Summarization
Video Summarization plays a vital role in the internet user's life, especially for those searching for user specified video of interest for a long time. In order to provide support for users in terms of searching and retrieving video content, it is necessary to segment the video into shots and extract representative frame of each shot which acts as a summary of the video. So, in this paper, an approach for shot boundary detection and keyframe extraction is proposed. To provide a better summarization of video, Local Binary Pattern (LBP) based feature extraction for detecting video shots is performed in order to identify objects motion information. Based on local maxima analysis, an efficient keyframe, which contains salient information of a shot is proposed. The performance of the proposed work is evaluated using evaluation metrics like Precision, Recall, and F1-Measure.
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