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Motion retrieval based on multi-view information and graph model

机译:基于多视图信息和图模型的运动检索

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摘要

Matching and retrieval of motion sequences has become an important research area in recent years, due to the increasing availability and popularity of motion capture data. In this paper, we propose a novel content-based method for retrieving of this human motion captured data. The proposed method includes two key steps, one is motion descriptor construction, and the other is retrieval based on query. Firstly, for representing motion by images, multi-view information is captured, and then switching liner dynamic system (SLDS) is built based on image fusion and light stream technology. Secondly, through inferring and coding of SLDS, a graph-based motion descriptor can be obtained. Lastly, based on proposed motion descriptor, the motion retrieval would be operated through direct matching between motion descriptors. Experiment results show our method is effectiveness.
机译:由于运动捕捉数据的可用性和普及度的提高,运动序列的匹配和检索已成为近年来的重要研究领域。在本文中,我们提出了一种新颖的基于内容的方法来检索此人体运动捕获的数据。所提出的方法包括两个关键步骤,一个是运动描述符的构造,另一个是基于查询的检索。首先,通过图像表示运动,捕获多视点信息,然后基于图像融合和光流技术建立开关衬板动态系统(SLDS)。其次,通过对SLDS的推断和编码,可以获得基于图的运动描述符。最后,基于提出的运动描述符,将通过运动描述符之间的直接匹配来进行运动检索。实验结果表明,该方法是有效的。

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