Efficient motion retrieval in large motion databases

Mubbasir Kapadia, I-Kao Chiang, Tiju Thomas, N. Badler, Joseph T. Kider
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引用次数: 118

Abstract

There has been a recent paradigm shift in the computer animation industry with an increasing use of pre-recorded motion for animating virtual characters. A fundamental requirement to using motion capture data is an efficient method for indexing and retrieving motions. In this paper, we propose a flexible, efficient method for searching arbitrarily complex motions in large motion databases. Motions are encoded using keys which represent a wide array of structural, geometric and, dynamic features of human motion. Keys provide a representative search space for indexing motions and users can specify sequences of key values as well as multiple combination of key sequences to search for complex motions. We use a trie-based data structure to provide an efficient mapping from key sequences to motions. The search times (even on a single CPU) are very fast, opening the possibility of using large motion data sets in real-time applications.
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大型运动数据库中的高效运动检索
最近,计算机动画行业出现了一种范式转变,即越来越多地使用预先录制的动作来制作虚拟角色动画。使用动作捕捉数据的一个基本要求是一种有效的索引和检索动作的方法。本文提出了一种在大型运动数据库中搜索任意复杂运动的灵活、高效的方法。运动是用键来编码的,这些键代表了人体运动的各种结构、几何和动态特征。键为索引运动提供了一个有代表性的搜索空间,用户可以指定键值序列以及键序列的多个组合来搜索复杂的运动。我们使用基于尝试的数据结构来提供从关键序列到运动的有效映射。搜索时间(即使在单个CPU上)非常快,这使得在实时应用程序中使用大型运动数据集成为可能。
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