基于关系图的视频抽象

Sulan Zhai, B. Luo, Jin Tang, Chunyan Zhang
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引用次数: 6

摘要

视频抽象在视频浏览、视频索引、视频检索等视频应用中起着重要的作用。本文提出了一种基于关系图表示的视频自动提取方法。首先,对视频序列中的所有帧构建关系图。其次,将图划分为不同的连通子图。再次,对数据集进行Isomap降维处理,并将Isomap的输出作为视频帧的特征向量。最后,引入模型选择混合模型,生成以各聚类中心为关键帧的细粒度视频抽象。在真实世界的视频集上进行了实验,获得了满意的视频抽象结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Video Abstraction Based on Relational Graphs
Video abstraction plays an important role in video browsing, video indexing, video retrieval and other video applications. In the paper, an automatic video abstraction method is developed based on relational graph representations. Firstly, a relational graph is constructed for all the frames in a video sequence. Secondly, the graph is partitioned into different connected subgraphs. Thirdly, Isomap is performed to reduce the dimensionality of the data set, and the output of Isomap is used as feature vector of the video frames. Lastly, a mixture model with model selection is introduced to generate the fine grain video abstraction with the centre of each clustering as the keyframes. Experiments are conducted on real world video sets with satisfying video abstraction results.
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