Similarity matching of arbitrarily shaped video by still shape features and shape deformations

B. Erol, F. Kossentini
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引用次数: 5

Abstract

The increasing availability of object-based video content requires new technologies for automatically extracting and matching of the low level features of arbitrarily shaped video. in this paper, we propose methods for the efficient retrieval of video object shapes. Our methods take into account not only the still shape features but also the shape deformations that may occur in the lifespan of video objects. We define a new shape similarity measure that is based on the shape similarity of the representative temporal instances of video objects. We also propose shape deformation features that are based on the variances of the still shape features. The proposed visual features can be derived directly from the MPEG-4 compressed domain or computed from the shape masks of the video objects in the spatial domain. Our experiments show that our proposed methods offer very good retrieval results.
基于静态形状特征和形状变形的任意形状视频相似度匹配
基于对象的视频内容越来越多,需要新的技术来自动提取和匹配任意形状视频的低级特征。在本文中,我们提出了一种高效检索视频对象形状的方法。我们的方法不仅考虑了静止的形状特征,而且考虑了在视频对象的生命周期中可能发生的形状变形。我们定义了一种新的基于视频对象的代表性时间实例的形状相似度的形状相似度度量。我们还提出了基于静态形状特征方差的形状变形特征。所提出的视觉特征可以直接从MPEG-4压缩域中获得,也可以从视频对象在空间域中的形状掩模中计算得到。实验结果表明,本文提出的方法具有很好的检索效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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