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An Efficient Algorithm for Content-Based Human Motion Retrieval

机译:一种基于内容的人体运动检索的高效算法

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摘要

With the development of motion capture techniques; more and more 3D motion libraries become available. The growing amount of motion capture data requires more efficient and effective methods for indexing, searching and retrieving. In many cases, the user will only have a sketchy idea of which kind of motion to look for in the motion database. In consequence, the description about the query movement is a bottleneck for motion retrieval system. This paper presents a framework that can describe and handle the query scenes effectively. Our content-based retrieval system supports two kinds of query modes: textual query mode and query-by-example mode. By using various kinds of qualitative features and adaptive segments of motion capture data stream, our indexing and retrieval methods are carried out at the segment level rather than at the frame level, making them quite efficient. Some experimental examples are given to demonstrate the effectiveness and efficiency of proposed algorithms.
机译:随着运动捕捉技术的发展;越来越多的3D运动库可用。越来越多的运动捕捉数据需要索引,搜索和检索的更有效的方法。在许多情况下,用户只会大致了解要在运动数据库中查找哪种运动。因此,有关查询运动的描述是运动检索系统的瓶颈。本文提出了一个可以有效描述和处理查询场景的框架。我们基于内容的检索系统支持两种查询模式:文本查询模式和按示例查询模式。通过使用各种定性特征和运动捕捉数据流的自适应段,我们的索引和检索方法是在段级别而不是帧级别执行的,这使它们非常有效。给出了一些实验示例,以证明所提出算法的有效性和效率。

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