A Motion Recognition Method by Using Primitive Motions
A Motion Recognition Method by Using Primitive Motions
复制标题
一种利用原始运动的运动识别方法
DOI：
10.1007/978-0-387-35504-7_8
复制
发表时间：
2000
期刊：
影响因子：
--
通讯作者：
K. Uehara
中科院分区：
文献类型：
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作者：
R. Osaki;M. Shimada;K. Uehara
基于内容的多媒体信息检索已在多个研究项目中进行了研究。在本文中，我们将重点研究人体运动数据的自动索引方法。我们将表示为 3D 位置时间序列的运动数据转换为符号序列。我们将这种方法称为转换自动索引。自动索引是通过模式匹配方法执行的。参考模式是模式匹配所必需的，因此我们将提出两种定义原始运动的方法来制作参考模式。第一种方法通过检测运动速度的变化将运动数据分割成分段运动数据。第二种方法对分段运动进行分类，使得相似的分段运动聚集在同一簇中。为了评估两个分段运动之间的相似性，我们使用动态时间规整（DTW）方法，因为即使同一个人执行相同的运动，每个分段运动也需要不同的时间长度。运动数据可以被转换成表示原始运动序列的符号序列。然后，使用连续动态规划（CDP）方法来识别运动内容。 CDP是DTW的扩展之一。它使我们能够轻松识别运动，即使它很复杂。
Contents-based retrieval of multimedia information has been investigated in several research projects. In this paper, we will focus on an automatic indexing method for human motion data. We convert a motion data, which is represented as time series of 3-D position, into a symbol sequence. We call this method as conversion automatic indexing. The automatic indexing is performed in a pattern matching approach. Reference patterns are necessary for pattern matching, so that we will propose two methods to define primitive motions in order to make reference patterns. The first method divides motion data into segmental motion data by detecting the change of motion speed. The second method classifies segmental motions such that similar segmental motions are gathered in the same cluster. In order to evaluate the similarity between two segmental motions, we use the Dynamic Time Warping (DTW) method because each segmental motion takes different time length even if the same person performed the same motions. Motion data can be converted into a symbol sequence which represents a sequence of primitive motions. Then, Continuous Dynamic Programming (CDP) method is used to recognize contents of motion. CDP is one of the extensions of DTW. It makes us possible to recognize a motion with ease even if it is complex.