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Motion Segment based on Sparse Representation and 3D Features

机译:基于稀疏表示和3D功能的运动段

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With the emergence of a large number of 3D human motion capture database, which makes how to efficiently analyze and process the data of human body movement, and make use of the motion capture database become a new challenge. In order to reduce the high dimensional complexity of the data, firstly, a 3D dimensional feature based on 3D spatial and temporal characteristics is extracted from the motion of the human body, then, the motion data is re-expressed by the use of method for sparse representation, and different motion types are separated from long motion sequences, so that a motion database used for subsequent motion recognition and retrieval can be established.
机译:随着大量3D人体运动捕获数据库的出现,这使得如何有效地分析和处理人体运动的数据,并利用运动捕获数据库成为一个新的挑战。 为了降低数据的高维度复杂度,首先,从人体的运动提取基于3D空间和时间特性的3D维度特征,然后,通过使用方法来重新表达运动数据 稀疏表示和不同的运动类型与长运动序列分离,从而可以建立用于后续运动识别和检索的运动数据库。

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